Activecontourmodel is a widely used method in visual tracking and image segmentation. Under the driven of objective function, the initial curve defined in activecontourmodel will evolve to a stable condition - a desired result in given image. As a typical region-based activecontourmodel, C-V model has a good effect on weak boundaries detection and anti noise ability which shows great potential in glacial lake extraction. Glacial lake is a sensitive indicator for reflecting global climate change, therefore accurate delineate glacial lake boundaries is essential to evaluate hydrologic environment and living environment. However, the current method in glacial lake extraction mainly contains water index method and recognition classification method are diffcult to directly applied in large scale glacial lake extraction due to the diversity of glacial lakes and masses impacted factors in the image, such as image noise, shadows, snow and ice, etc. Regarding the abovementioned advantanges of C-V model and diffcults in glacial lake extraction, we introduce the signed pressure force function to improve the C-V model for adapting to processing of glacial lake extraction. To inspect the effect of glacial lake extraction results, three typical glacial lake development sites were selected, include Altai mountains, Centre Himalayas, South-eastern Tibet, and Landsat8 OLI imagery was conducted as experiment data source, Google earth imagery as reference data for varifying the results. The experiment consequence suggests that improved activecontourmodel we proposed can effectively discriminate the glacial lakes from complex backgound with a higher Kappa Coefficient - 0.895, especially in some small glacial lakes which belongs to weak information in the image. Our finding provide a new approach to improved accuracy under the condition of large proportion of small glacial lakes and the possibility for automated glacial lake mapping in large-scale area.

Extracting the shape of the gallbladder from an ultrasonography (US) image allows superfluous information which is immaterial in the diagnostic process to be eliminated. In this project an activecontourmodel was used to extract the shape of the gallbladder, both for cases free of lesions, and for those showing specific disease units, namely: lithiasis, polyps and changes in the shape of the organ, such as folds or turns of the gallbladder. The approximate shape of the gallbladder was found by applying the motion equation model. The tests conducted have shown that for the 220 US images of the gallbladder, the area error rate (AER) amounted to 18.15%.

Skull defects result in brain infection and inadequate brain protection and pose a general danger to patient health. To avoid these situations and prevent re-injury, a prosthesis must be constructed and grafted onto the deficient region. With the development of rapid customization through additive manufacturing and 3D printing technology, skull prostheses can be fabricated accurately and efficiently prior to cranioplasty. However, an unfitted skull prosthesis made with a metal implant can cause repeated infection, potentially necessitating secondary surgery. This paper presents a method of creating suitably geometric graphics of skull defects to be applied in skull repair through activecontourmodels. These models can be adjusted in each computed tomography slice according to the graphic features, and the curves representing the skull defect can be modeled. The generated graphics can adequately mimic the natural curvature of the complete skull. This method will enable clinical surgeons to rapidly implant customized prostheses, which is of particular importance in emergency surgery. The findings of this research can help surgeons provide patients with skull defects with treatment of the highest quality.

The purpose of this study was to develop a computer vision method to measure geometric parameters of the weld pool in a deep penetration CO 2 laser welding system. Accurate measurement was achieved by removing a huge amount of interference caused by spatter, arc light and plasma to extract the true weld pool contour. This paper introduces a closed convex activecontour (CCAC) model derived from the activecontourmodel (snake model), which is a more robust high-level vision method than the traditional low-level vision methods. We made an improvement by integrating an activecontour with the information that the weld pool contour is almost a closed convex curve. An effective thresholding method and an improved greedy algorithm are also given to complement the CCAC model. These influences can be effectively removed by using the CCAC model to acquire and measure the weld pool contour accurately and relatively fast. (paper)

This paper presents a fully automated approach to detect the intima and media-adventitia borders in intravascular ultrasound images based on parametric activecontourmodels. To detect the intima border, we compute a new image feature applying a combination of short-term autocorrelations calculated for the contour pixels. These feature values are employed to define an energy function of the activecontour called normalized cumulative short-term autocorrelation. Exploiting this energy function, the intima border is separated accurately from the blood region contaminated by high speckle noise. To extract media-adventitia boundary, we define a new form of energy function based on edge, texture and spring forces for the activecontour. Utilizing this activecontour, the media-adventitia border is identified correctly even in presence of branch openings and calcifications. Experimental results indicate accuracy of the proposed methods. In addition, statistical analysis demonstrates high conformity between manual tracing and the results obtained by the proposed approaches.

The detection of pedestrians in real-world scenes is a daunting task, especially in crowded situations. Our experience over the last years has shown that active shape models (ASM) can contribute significantly to a robust pedestrian detection system. The paper starts with an overview of shape model approaches, it then explains our approach which builds on top of Eigenshape models which have been trained using real-world data. These models are placed over candidate regions and matched to image gradients using a scoring function which integrates i) point distribution, ii) local gradient orientations iii) local image gradient strengths. A matching and shape model update process is iteratively applied in order to fit the flexible models to the local image content. The weights of the scoring function have a significant impact on the ASM performance. We analyze different settings of scoring weights for gradient magnitude, relative orientation differences, distance between model and gradient in an experiment which uses real-world data. Although for only one pedestrian model in an image computation time is low, the number of necessary processing cycles which is needed to track many people in crowded scenes can become the bottleneck in a real-time application. We describe the measures which have been taken in order to improve the speed of the ASM implementation and make it real-time capable.

Full Text Available We present a nonparametric shape constrained algorithm for segmentation of coronary arteries in computed tomography images within the framework of activecontours. An adaptive scale selection scheme, based on the global histogram information of the image data, is employed to determine the appropriate window size for each point on the activecontour, which improves the performance of the activecontourmodel in the low contrast local image regions. The possible leakage, which cannot be identified by using intensity features alone, is reduced through the application of the proposed shape constraint, where the shape of circular sampled intensity profile is used to evaluate the likelihood of current segmentation being considered vascular structures. Experiments on both synthetic and clinical datasets have demonstrated the efficiency and robustness of the proposed method. The results on clinical datasets have shown that the proposed approach is capable of extracting more detailed coronary vessels with subvoxel accuracy.

Gradient vector flow (GVF) is an important external force field for activecontourmodels. Various vector fields based on GVF have been proposed. However, these vector fields are obtained with many iterations and have difficulty in capturing the whole image area. On the other hand, the ability to converge to deep and complex concavity with these vector fields is also needed to improve. In this paper, by analyzing the diffusion equation of GVF, a normalized set is defined and a dynamically nor...

The advances in 3D data modelling methods are becoming increasingly popular in the areas of biology, chemistry and medical applications. The Nuclear Magnetic Resonance Imaging (NMRI) technique has progressed at a spectacular rate over the past few years, its uses have been spread over many applications throughout the body in both anatomical and functional investigations. In this paper we present the application of Zernike polynomials for 3D mesh model of the head using the contour acquired of cross-sectional slices by activecontourmodel extraction and we propose the visualization with OpenGL 3D Graphics of the 2D-3D (slice-surface) information for the diagnostic aid in medical applications.

One of the attractive image segmentation methods is the ActiveContourModel (ACM) which has been widely used in medical imaging as it always produces sub-regions with continuous boundaries. Intravascular ultrasound (IVUS) is a catheter based medical imaging technique which is used for quantitative assessment of atherosclerotic disease. Two methods of ACM realizations are presented in this paper. The gradient descent flow based on minimizing energy functional can be used for segmentation of IVUS images. However this local operation alone may not be adequate to work with the complex IVUS images. The first method presented consists of basically combining the local geodesic activecontours and global region-based activecontours. The advantage of combining the local and global operations is to allow curves deforming under the energy to find only significant local minima and delineate object borders despite noise, poor edge information and heterogeneous intensity profiles. Results for this algorithm are compared to standard techniques to demonstrate the method's robustness and accuracy. In the second method, the energy function is appropriately modified and minimized using a Hopfield neural network. Proper modifications in the definition of the bias of the neurons have been introduced to incorporate image characteristics. The method overcomes distortions in the expected image pattern, such as due to the presence of calcium, and employs a specialized structure of the neural network and boundary correction schemes which are based on a priori knowledge about the vessel geometry. The presented method is very fast and has been evaluated using sequences of IVUS frames.

Purpose: Although positron emission tomography (PET) images have shown potential to improve the accuracy of targeting in radiation therapy planning and assessment of response to treatment, the boundaries of tumors are not easily distinguishable from surrounding normal tissue owing to the low spatial resolution and inherent noisy characteristics of PET images. The objective of this study is to develop a generic and robust method for automatic delineation of tumor volumes using an activecontourmodel and to evaluate its performance using phantom and clinical studies. Methods: MASAC, a method for automatic segmentation using an activecontourmodel, incorporates the histogram fuzzy C-means clustering, and localized and textural information to constrain the activecontour to detect boundaries in an accurate and robust manner. Moreover, the lattice Boltzmann method is used as an alternative approach for solving the level set equation to make it faster and suitable for parallel programming. Twenty simulated phantom studies and 16 clinical studies, including six cases of pharyngolaryngeal squamous cell carcinoma and ten cases of nonsmall cell lung cancer, were included to evaluate its performance. Besides, the proposed method was also compared with the contourlet-based activecontour algorithm (CAC) and Schaefer’s thresholding method (ST). The relative volume error (RE), Dice similarity coefficient (DSC), and classification error (CE) metrics were used to analyze the results quantitatively. Results: For the simulated phantom studies (PSs), MASAC and CAC provide similar segmentations of the different lesions, while ST fails to achieve reliable results. For the clinical datasets (2 cases with connected high-uptake regions excluded) (CSs), CAC provides for the lowest mean RE (−8.38% ± 27.49%), while MASAC achieves the best mean DSC (0.71 ± 0.09) and mean CE (53.92% ± 12.65%), respectively. MASAC could reliably quantify different types of lesions assessed in this work

Recent research has suggested that the measurement of regional atrophy in the structure of the medial temporal lobe is a promising way to discriminate Alzheimer-type dementia patients from healthy control subjects. There are some reports that the inferior horns of the lateral ventricles are expanded by atrophying the structure of the medial temporal lobe. We developed a technique to automatically detect the region of the inferior horns of the lateral ventricles by gray-level thresholding and morphological processing. However, there were some incorrect regions in this method. Accordingly, we proposed a technique for which activecontourmodels (ACM) were used. Our ACM incorporates the improved edge-based image and the external constraint to improve convergence and to reduce its dependence on initial estimation. In this study, we present the details of an algorithm that traces the contours of the inferior horns of the lateral ventricles and its performance relative to manual methods. The average degree of correspondence between the extract region and manual trace was measured in 30 inferior horns of 15 subjects. The average degree of correspondence of the proposed method was about 4% higher than that of the conventional method. These results suggest that the proposed method is more accurate than the conventional method. (author)

Automatic abnormality detection in Magnetic Resonance Imaging (MRI) is an important issue in many diagnostic and therapeutic applications. Here an automatic brain tumor detection method is introduced that uses T1-weighted images and K. Zhang et. al.'s activecontourmodel driven by local image fitting (LIF) energy. Local image fitting energy obtains the local image information, which enables the algorithm to segment images with intensity inhomogeneities. Advantage of this method is that the LIF energy functional has less computational complexity than the local binary fitting (LBF) energy functional; moreover, it maintains the sub-pixel accuracy and boundary regularization properties. In Zhang's algorithm, a new level set method based on Gaussian filtering is used to implement the variational formulation, which is not only vigorous to prevent the energy functional from being trapped into local minimum, but also effective in keeping the level set function regular. Experiments show that the proposed method achieves high accuracy brain tumor segmentation results.

A CAD tool for chest radiographs consists of several procedures and the very first step is segmentation of lung fields. We develop a novel methodology for segmentation of lung fields in chest radiographs that can satisfy the following two requirements. First, we aim to develop a segmentation method that does not need a training stage with manual estimation of anatomical features in a large training dataset of images. Secondly, for the ease of implementation, it is desirable to apply a well established model that is widely used for various image-partitioning practices. The Chan-Vese activecontourmodel, which is based on Mumford-Shah functional in the level set framework, is applied for segmentation of lung fields. With the use of this model, segmentation of lung fields can be carried out without detailed prior knowledge on the radiographic anatomy of the chest, yet in some chest radiographs, the trachea regions are unfavorably segmented out in addition to the lung field contours. To eliminate artifacts from the trachea, we locate the upper end of the trachea, find a vertical center line of the trachea and delineate it, and then brighten the trachea region to make it less distinctive. The segmentation process is finalized by subsequent morphological operations. We randomly select 30 images from the Japanese Society of Radiological Technology image database to test the proposed methodology and the results are shown. We hope our segmentation technique can help to promote of CAD tools, especially for emerging chest radiographic imaging techniques such as dual energy radiography and chest tomosynthesis.

Numerical instability often occurs in evolving of parametric activecontours. This is mainly due to the undesired change of parametrization during evolution. In this paper, we propose a new tangential diffusion term to compensate this undesired change. As a result, the parametrization will converge...

state equation). The contour evolution is implemented in the framework of level sets. Finally, the proposed method is validated on various examples. We focus among others in the segmentation of calcified plaques observed in radiographs from human lumbar aortic regions. Keywords Segmentation - Inpainting - Active...

Full Text Available After the characteristics of geodesic activecontourmodel (GAC, Chan-Vese model(CV and local binary fitting model(LBF are analyzed, and the activecontourmodel based on regions and edges is combined with image segmentation method based on quad-tree, a waterline extraction method based on quad-tree and multiple activecontourmodel is proposed in this paper. Firstly, the method provides an initial contour according to quad-tree segmentation. Secondly, a new signed pressure force(SPF function based on global image statistics information of CV model and local image statistics information of LBF model has been defined, and then ,the edge stopping function(ESF is replaced by the proposed SPF function, which solves the problem such as evolution stopped in advance and excessive evolution. Finally, the selective binary and Gaussian filtering level set method is used to avoid reinitializing and regularization to improve the evolution efficiency. The experimental results show that this method can effectively extract the weak edges and serious concave edges, and owns some properties such as sub-pixel accuracy, high efficiency and reliability for waterline extraction.

Highway extraction and vehicle detection are two of the most important steps in traffic-flow analysis from multi-frame aerial photographs. The traditional method of deriving traffic flow trajectories relies on manual vehicle counting from a sequence of aerial photographs, which is tedious and time-consuming. This research presents a new framework for semi-automatic highway extraction. The basis of the new framework is an improved geometric activecontour (GAC) model. This novel model seeks to minimize an objective function that transforms a problem of propagation of regular curves into an optimization problem. The implementation of curve propagation is based on level set theory. By using an implicit representation of a two-dimensional curve, a level set approach can be used to deal with topological changes naturally, and the output is unaffected by different initial positions of the curve. However, the original GAC model, on which the new model is based, only incorporates boundary information into the curve propagation process. An error-producing phenomenon called leakage is inevitable wherever there is an uncertain weak edge. In this research, region-based information is added as a constraint into the original GAC model, thereby, giving this proposed method the ability of integrating both boundary and region-based information during the curve propagation. Adding the region-based constraint eliminates the leakage problem. This dissertation applies the proposed augmented GAC model to the problem of highway extraction from high-resolution aerial photography. First, an optimized stopping criterion is designed and used in the implementation of the GAC model. It effectively saves processing time and computations. Second, a seed point propagation framework is designed and implemented. This framework incorporates highway extraction, tracking, and linking into one procedure. A seed point is usually placed at an end node of highway segments close to the boundary of the

While the popular thin layer scanning technology of spiral CT has helped to improve diagnoses of lung diseases, the large volumes of scanning images produced by the technology also dramatically increase the load of physicians in lesion detection. Computer-aided diagnosis techniques like lesions segmentation in thin CT sequences have been developed to address this issue, but it remains a challenge to achieve high segmentation efficiency and accuracy without much involvement of human manual intervention. In this paper, we present our research on automated segmentation of lung parenchyma with an improved geodesic activecontourmodel that is geodesic activecontourmodel based on similarity (GACBS). Combining spectral clustering algorithm based on Nystrom (SCN) with GACBS, this algorithm first extracts key image slices, then uses these slices to generate an initial contour of pulmonary parenchyma of un-segmented slices with an interpolation algorithm, and finally segments lung parenchyma of un-segmented slices. Experimental results show that the segmentation results generated by our method are close to what manual segmentation can produce, with an average volume overlap ratio of 91.48%.

This research work is aimed to develop autonomous bio-monitoring mobile robots, which are capable of tracking and measuring patients' motions, recognizing the patients' behavior based on observation data, and providing calling for medical personnel in emergency situations in home environment. The robots to be developed will bring about cost-effective, safe and easier at-home rehabilitation to most motor-function impaired patients (MIPs). In our previous research, a full framework was established towards this research goal. In this research, we aimed at improving the human activity recognition by using contour data of the tracked human subject extracted from the depth images as the signal source, instead of the lower limb joint angle data used in the previous research, which are more likely to be affected by the motion of the robot and human subjects. Several geometric parameters, such as, the ratio of height to weight of the tracked human subject, and distance (pixels) between centroid points of upper and lower parts of human body, were calculated from the contour data, and used as the features for the activity recognition. A Hidden Markov Model (HMM) is employed to classify different human activities from the features. Experimental results showed that the human activity recognition could be achieved with a high correct rate.

Purpose: To develop and evaluate a computerized semiautomatic segmentation method for accurate extraction of three-dimensional lesions from dynamic contrast-enhanced magnetic resonance images (DCE-MRIs) of the breast. Methods: The authors propose a new background distribution-based activecontourmodel using level set (BDACMLS) to segment lesions in breast DCE-MRIs. The method starts with manual selection of a region of interest (ROI) that contains the entire lesion in a single slice where the lesion is enhanced. Then the lesion volume from the volume data of interest, which is captured automatically, is separated. The core idea of BDACMLS is a new signed pressure function which is based solely on the intensity distribution combined with pathophysiological basis. To compare the algorithm results, two experienced radiologists delineated all lesions jointly to obtain the ground truth. In addition, results generated by other different methods based on level set (LS) are also compared with the authors’ method. Finally, the performance of the proposed method is evaluated by several region-based metrics such as the overlap ratio. Results: Forty-two studies with 46 lesions that contain 29 benign and 17 malignant lesions are evaluated. The dataset includes various typical pathologies of the breast such as invasive ductal carcinoma, ductal carcinomain situ, scar carcinoma, phyllodes tumor, breast cysts, fibroadenoma, etc. The overlap ratio for BDACMLS with respect to manual segmentation is 79.55% ± 12.60% (mean ± s.d.). Conclusions: A new activecontourmodel method has been developed and shown to successfully segment breast DCE-MRI three-dimensional lesions. The results from this model correspond more closely to manual segmentation, solve the weak-edge-passed problem, and improve the robustness in segmenting different lesions.

Activecontourmodel (ACM) has been one of the most widely utilized methods in magnetic resonance (MR) brain image segmentation because of its ability of capturing topology changes. However, most of the existing ACMs only consider single-slice information in MR brain image data, i.e., the information used in ACMs based segmentation method is extracted only from one slice of MR brain image, which cannot take full advantage of the adjacent slice images' information, and cannot satisfy the local segmentation of MR brain images. In this paper, a novel ACM is proposed to solve the problem discussed above, which is based on multi-variate local Gaussian distribution and combines the adjacent slice images' information in MR brain image data to satisfy segmentation. The segmentation is finally achieved through maximizing the likelihood estimation. Experiments demonstrate the advantages of the proposed ACM over the single-slice ACM in local segmentation of MR brain image series.

Full Text Available Segmentation of the left atrium (LA from cardiac magnetic resonance imaging (MRI datasets is of great importance for image guided atrial fibrillation ablation, LA fibrosis quantification, and cardiac biophysical modelling. However, automated LA segmentation from cardiac MRI is challenging due to limited image resolution, considerable variability in anatomical structures across subjects, and dynamic motion of the heart. In this work, we propose a combined random forests (RFs and activecontourmodel (ACM approach for fully automatic segmentation of the LA from cardiac volumetric MRI. Specifically, we employ the RFs within an autocontext scheme to effectively integrate contextual and appearance information from multisource images together for LA shape inferring. The inferred shape is then incorporated into a volume-scalable ACM for further improving the segmentation accuracy. We validated the proposed method on the cardiac volumetric MRI datasets from the STACOM 2013 and HVSMR 2016 databases and showed that it outperforms other latest automated LA segmentation methods. Validation metrics, average Dice coefficient (DC and average surface-to-surface distance (S2S, were computed as 0.9227±0.0598 and 1.14±1.205 mm, versus those of 0.6222–0.878 and 1.34–8.72 mm, obtained by other methods, respectively.

Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, activecontourmodel (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging.

Gliomas are tumours arising from the interstitial tissue of the brain which are heterogeneous, infiltrative and possess ill-defined borders. Tumour subregions (e.g. solid enhancing part, edema and necrosis) are often used for tumour characterisation. Tumour demarcation into substructures facilitates glioma staging and provides essential information. Manual segmentation had several drawbacks that include laborious, time consuming, subjected to intra and inter-rater variability and hindered by diversity in the appearance of tumour tissues. In this work, activecontourmodel (ACM) was used to segment the solid enhancing subregion of the tumour. 2D brain image acquisition data using 3T MRI fast spoiled gradient echo sequence in post gadolinium of four histologically proven high-grade glioma patients were obtained. Preprocessing of the images which includes subtraction and skull stripping were performed and then followed by ACM segmentation. The results of the automatic segmentation method were compared against the manual delineation of the tumour by a trainee radiologist. Both results were further validated by an experienced neuroradiologist and a brief quantitative evaluations (pixel area and difference ratio) were performed. Preliminary results of the clinical data showed the potential of ACM model in the application of fast and large scale tumour segmentation in medical imaging. (paper)

Full Text Available It is often a difficult task to accurately segment brain magnetic resonance (MR images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%.

Full Text Available This paper presents a novel automatic image segmentation method based on the theory of activecontourmodels and estimation of distribution algorithms. The proposed method uses the univariate marginal distribution model to infer statistical dependencies between the control points on different activecontours. These contours have been generated through an alignment process of reference shape priors, in order to increase the exploration and exploitation capabilities regarding different interactive segmentation techniques. This proposed method is applied in the segmentation of the hollow core in microscopic images of photonic crystal fibers and it is also used to segment the human heart and ventricular areas from datasets of computed tomography and magnetic resonance images, respectively. Moreover, to evaluate the performance of the medical image segmentations compared to regions outlined by experts, a set of similarity measures has been adopted. The experimental results suggest that the proposed image segmentation method outperforms the traditional activecontourmodel and the interactive Tseng method in terms of segmentation accuracy and stability.

In this paper, we present a framework for activecontour-based visual tracking using level sets. The main components of our framework include contour-based tracking initialization, color-based contour evolution, adaptive shape-based contour evolution for non-periodic motions, dynamic shape-based contour evolution for periodic motions, and the handling of abrupt motions. For the initialization of contour-based tracking, we develop an optical flow-based algorithm for automatically initializing contours at the first frame. For the color-based contour evolution, Markov random field theory is used to measure correlations between values of neighboring pixels for posterior probability estimation. For adaptive shape-based contour evolution, the global shape information and the local color information are combined to hierarchically evolve the contour, and a flexible shape updating model is constructed. For the dynamic shape-based contour evolution, a shape mode transition matrix is learnt to characterize the temporal correlations of object shapes. For the handling of abrupt motions, particle swarm optimization is adopted to capture the global motion which is applied to the contour in the current frame to produce an initial contour in the next frame.

Full Text Available The accurate segmentation of pulmonary nodules is an important preprocessing step in computer-aided diagnoses of lung cancers. However, the existing segmentation methods may cause the problem of edge leakage and cannot segment juxta-vascular pulmonary nodules accurately. To address this problem, a novel automatic segmentation method based on an LBF activecontourmodel with information entropy and joint vector is proposed in this paper. Our method extracts the interest area of pulmonary nodules by a standard uptake value (SUV in Positron Emission Tomography (PET images, and automatic threshold iteration is used to construct an initial contour roughly. The SUV information entropy and the gray-value joint vector of Positron Emission Tomography–Computed Tomography (PET-CT images are calculated to drive the evolution of contour curve. At the edge of pulmonary nodules, evolution will be stopped and accurate results of pulmonary nodule segmentation can be obtained. Experimental results show that our method can achieve 92.35% average dice similarity coefficient, 2.19 mm Hausdorff distance, and 3.33% false positive with the manual segmentation results. Compared with the existing methods, our proposed method that segments juxta-vascular pulmonary nodules in PET-CT images is more accurate and efficient.

In this paper, we present a fully automated approach to coronary vessel segmentation, which involves calcification or soft plaque delineation in addition to accurate lumen delineation, from 3D Cardiac Computed Tomography Angiography data. Adequately virtualizing the coronary lumen plays a crucial role for simulating blood ow by means of fluid dynamics while additionally identifying the outer vessel wall in the case of arteriosclerosis is a prerequisite for further plaque compartment analysis. Our method is a hybrid approach complementing ActiveContourModel-based segmentation with an external image force that relies on a Random Forest Regression model generated off-line. The regression model provides a strong estimate of the distance to the true vessel surface for every surface candidate point taking into account 3D wavelet-encoded contextual image features, which are aligned with the current surface hypothesis. The associated external image force is integrated in the objective function of the activecontourmodel, such that the overall segmentation approach benefits from the advantages associated with snakes and from the ones associated with machine learning-based regression alike. This yields an integrated approach achieving competitive results on a publicly available benchmark data collection (Rotterdam segmentation challenge).

Full Text Available Document analysis of images snapped by camera is a growing challenge. These photos are often poor-quality compound images, composed of various objects and text; this makes automatic analysis complicated. OCR is one of the image processing techniques which is used to perform automatic identification of texts. Existing image processing techniques need to manage many parameters in order to clearly recognize the text in such pictures. Segmentation is regarded one of these essential parameters. This paper discusses the accuracy of segmentation process and its effect over the recognition process. According to the proposed method, the images were firstly filtered using the wiener filter then the activecontour algorithm could be applied in the segmentation process. The Tesseract OCR Engine was selected in order to evaluate the performance and identification accuracy of the proposed method. The results showed that a more accurate segmentation process shall lead to a more accurate recognition results. The rate of recognition accuracy was 0.95 for the proposed algorithm compared with 0.85 for the Tesseract OCR Engine.

Definition of the optimal training set for the automated segmentation of short-axis left ventricular magnetic resonance (MR) imaging studies in clinical practice based on active appearance model (AAM). We investigated the segmentation accuracy by varying the size and composition of the training set

The large amount of data generated in biological experiments that rely on advanced microscopy can be handled only with automated image analysis. Most analyses require a reliable cell image segmentation eventually capable of detecting subcellular structures.We present an automatic segmentation method to detect Polycomb group (PcG) proteins areas isolated from nuclei regions in high-resolution fluorescent cell image stacks. It combines two segmentation algorithms that use an activecontourmodel and a classification technique serving as a tool to better understand the subcellular three-dimensional distribution of PcG proteins in live cell image sequences. We obtained accurate results throughout several cell image datasets, coming from different cell types and corresponding to different fluorescent labels, without requiring elaborate adjustments to each dataset.

Activecontour and active polygon models have been used widely for image segmentation. In some applications, the topology of the object(s) to be detected from an image is known a priori, despite a complex unknown geometry, and it is important that the activecontour or polygon maintain the desired topology. In this work, we construct a novel geometric flow that can be added to image-based evolutions of activecontours and polygons in order to preserve the topology of the initial contour or polygon. We emphasize that, unlike other methods for topology preservation, the proposed geometric flow continually adjusts the geometry of the original evolution in a gradual and graceful manner so as to prevent a topology change long before the curve or polygon becomes close to topology change. The flow also serves as a global regularity term for the evolving contour, and has smoothness properties similar to curvature flow. These properties of gradually adjusting the original flow and global regularization prevent geometrical inaccuracies common with simple discrete topology preservation schemes. The proposed topology preserving geometric flow is the gradient flow arising from an energy that is based on electrostatic principles. The evolution of a single point on the contour depends on all other points of the contour, which is different from traditional curve evolutions in the computer vision literature.

Full Text Available Research works dealing with computational methods for roads extraction have considerably increased in the latest two decades. This procedure is usually performed on optical or microwave sensors (radar imagery. Radar images offer advantages when compared to optical ones, for they allow the acquisition of scenes regardless of atmospheric and illumination conditions, besides the possibility of surveying regions where the terrain is hidden by the vegetation canopy, among others. The cartographic mapping based on these images is often manually accomplished, requiring considerable time and effort from the human interpreter. Maps for detecting new roads or updating the existing roads network are among the most important cartographic products to date. There are currently many studies involving the extraction of roads by means of automatic or semi-automatic approaches. Each of them presents different solutions for different problems, making this task a scientific issue still open. One of the preliminary steps for roads extraction can be the seeding of points belonging to roads, what can be done using different methods with diverse levels of automation. The identified seed points are interpolated to form the initial road network, and are hence used as an input for an extraction method properly speaking. The present work introduces an innovative hybrid method for the extraction of roads centre-axis in a synthetic aperture radar (SAR airborne image. Initially, candidate points are fully automatically seeded using Self-Organizing Maps (SOM, followed by a pruning process based on specific metrics. The centre-axis are then detected by an open-curve activecontourmodel (snakes. The obtained results were evaluated as to their quality with respect to completeness, correctness and redundancy.

Most ActiveContourModels (ACMs) deal with the image segmentation problem as a functional optimization problem, as they work on dividing an image into several regions by optimizing a suitable functional. Among ACMs, variational level set methods have been used to build an activecontour with the aim of modeling arbitrarily complex shapes. Moreover, they can handle also topological changes of the contours. Self-Organizing Maps (SOMs) have attracted the attention of many computer vision scientists, particularly in modeling an activecontour based on the idea of utilizing the prototypes (weights) of a SOM to control the evolution of the contour. SOM-based models have been proposed in general with the aim of exploiting the specific ability of SOMs to learn the edge-map information via their topology preservation property and overcoming some drawbacks of other ACMs, such as trapping into local minima of the image energy functional to be minimized in such models. In this survey, we illustrate the main concepts of variational level set-based ACMs, SOM-based ACMs, and their relationship and review in a comprehensive fashion the development of their state-of-the-art models from a machine learning perspective, with a focus on their strengths and weaknesses. PMID:25960736

Accurate lung segmentation from high resolution CT images is a challenging task due to various detail tracheal structures, missing boundary segments and complex lung anatomy. One popular method is based on gray-level threshold, however its results are usually rough. A united geometric activecontoursmodel based on level set is proposed for lung segmentation in this paper. Particularly, this method combines local boundary information and region statistical-based model synchronously: 1) Boundary term ensures the integrality of lung tissue.2) Region term makes the level set function evolve with global characteristic and independent on initial settings. A penalizing energy term is introduced into the model, which forces the level set function evolving without re-initialization. The method is found to be much more efficient in lung segmentation than other methods that are only based on boundary or region. Results are shown by 3D lung surface reconstruction, which indicates that the method will play an important role in the design of computer-aided diagnostic (CAD) system.

Full Text Available In this paper we discuss a classic clustering algorithm that can be used to segment images and a recently developed activecontour image segmentation model. We propose integrating aspects of the classic algorithm to improve the activecontourmodel. For the resulting CVK and B-means segmentation algorithms we examine methods to decrease the size of the image domain. The CVK method has been implemented to run on parallel and distributed computers. By changing the order of updating the pixels, it was possible to replace synchronous communication with asynchronous communication and subsequently the parallel efficiency is improved.

Full Text Available Abstract We present a method to improve the accuracy and speed, as well as significantly reduce the memory requirements, for the recently proposed Graph Partitioning ActiveContours (GPACs algorithm for image segmentation in the work of Sumengen and Manjunath (2006. Instead of computing an approximate but still expensive dissimilarity matrix of quadratic size, , for a 2D image of size and regular image tiles of size , we use fixed length histograms and an intensity-based symmetric-centrosymmetric extensor matrix to jointly compute terms associated with the complete dissimilarity matrix. This computationally efficient reformulation of GPAC using a very small memory footprint offers two distinct advantages over the original implementation. It speeds up convergence of the evolving activecontour and seamlessly extends performance of GPAC to multidimensional images.

This paper presents a new image segmentation method based on multiple activecontours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical activecontourmodel. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical activecontourmodel and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation. PMID:23983809

Full Text Available This paper presents a new image segmentation method based on multiple activecontours guided by differential evolution, called MACDE. The segmentation method uses differential evolution over a polar coordinate system to increase the exploration and exploitation capabilities regarding the classical activecontourmodel. To evaluate the performance of the proposed method, a set of synthetic images with complex objects, Gaussian noise, and deep concavities is introduced. Subsequently, MACDE is applied on datasets of sequential computed tomography and magnetic resonance images which contain the human heart and the human left ventricle, respectively. Finally, to obtain a quantitative and qualitative evaluation of the medical image segmentations compared to regions outlined by experts, a set of distance and similarity metrics has been adopted. According to the experimental results, MACDE outperforms the classical activecontourmodel and the interactive Tseng method in terms of efficiency and robustness for obtaining the optimal control points and attains a high accuracy segmentation.

This paper presents a novel image segmentation method based on multiple activecontours driven by particle swarm optimization (MACPSO). The proposed method uses particle swarm optimization over a polar coordinate system to increase the energy-minimizing capability with respect to the traditional activecontourmodel. In the first stage, to evaluate the robustness of the proposed method, a set of synthetic images containing objects with several concavities and Gaussian noise is presented. Subsequently, MACPSO is used to segment the human heart and the human left ventricle from datasets of sequential computed tomography and magnetic resonance images, respectively. Finally, to assess the performance of the medical image segmentations with respect to regions outlined by experts and by the graph cut method objectively and quantifiably, a set of distance and similarity metrics has been adopted. The experimental results demonstrate that MACPSO outperforms the traditional activecontourmodel in terms of segmentation accuracy and stability. PMID:23762177

In this paper, we will study the following pattern recognition problem: Every pattern is a 3-dimensional graph, its surface can be split up into some regions, every region is composed of the pixels with the approximately same colour value and the approximately same depth value that is distance to eyes, and there may also be some contours, e.g., literal contours, on a surface of every pattern. For this problem we reveal the inherent laws. Moreover, we establish a cognitive model to reflect the...

Measurement of lung ventilation is one of the most reliable techniques in diagnosing pulmonary diseases. The time-consuming and bias-prone traditional methods using hyperpolarized H 3 He and 1 H magnetic resonance imageries have recently been improved by an automated technique based on 'multiple activecontour evolution'. This method involves a simultaneous evolution of multiple initial conditions, called 'snakes', eventually leading to their 'merging' and is entirely independent of the shapes and sizes of snakes or other parametric details. The objective of this paper is to show, through a theoretical analysis, that the functional dynamics of merging as depicted in the activecontour method has a direct analogue in statistical physics and this explains its 'universality'. We show that the multiple activecontour method has an universal scaling behaviour akin to that of classical nucleation in two spatial dimensions. We prove our point by comparing the numerically evaluated exponents with an equivalent thermodynamic model

Full Text Available An automatic approach to detect bilge dumping in synthetic aperture radar (SAR) images over Southern African oceans is proposed. The approach uses a threshold-based algorithm and a region-based activecontourmodel (ACM) algorithm to achieve...

Full Text Available Because of cross-disciplinary nature, ActiveContourmodeling techniques have been utilized extensively for the image segmentation. In traditional activecontour based segmentation techniques based on level set methods, the energy functions are defined based on the intensity gradient. This makes them highly sensitive to the situation where the underlying image content is characterized by image nonhomogeneities due to illumination and contrast condition. This is the most difficult problem to make them as fully automatic image segmentation techniques. This paper introduces one of the approaches based on image enhancement to this problem. The enhanced image is obtained using NonSubsampled Contourlet Transform, which improves the edges strengths in the direction where the illumination is not proper and then activecontourmodel based on level set technique is utilized to segment the object. Experiment results demonstrate that proposed method can be utilized along with existing activecontourmodel based segmentation method under situation characterized by intensity non-homogeneity to make them fully automatic.

This paper proposes a relative pose estimation approach based on object contourmodel. The first step is to obtain a two-dimensional (2D) projection of three-dimensional (3D)-model-based target, which will be divided into 40 forms by clustering and LDA analysis. Then we proceed by extracting the target contour in each image and computing their Pseudo-Zernike Moments (PZM), thus a model library is constructed in an offline mode. Next, we spot a projection contour that resembles the target silhouette most in the present image from the model library with reference of PZM; then similarity transformation parameters are generated as the shape context is applied to match the silhouette sampling location, from which the identification parameters of target can be further derived. Identification parameters are converted to relative pose parameters, in the premise that these values are the initial result calculated via iterative refinement algorithm, as the relative pose parameter is in the neighborhood of actual ones. At last, Distance Image Iterative Least Squares (DI-ILS) is employed to acquire the ultimate relative pose parameters.

Full Text Available We propose a novel activecontourmodel in a variational level set formulation for image segmentation and target localization. We combine a local image fitting term and a global image fitting term to drive the contour evolution. Our model can efficiently segment the images with intensity inhomogeneity with the contour starting anywhere in the image. In its numerical implementation, an efficient numerical schema is used to ensure sufficient numerical accuracy. We validated its effectiveness in numerous synthetic images and real images, and the promising experimental results show its advantages in terms of accuracy, efficiency, and robustness.

The majority of state of the art segmentation algorithms are able to give proper results in healthy organs but not in pathological ones. However, many clinical applications require an accurate segmentation of pathological organs. The determination of the target boundaries for radiotherapy or liver volumetry calculations are examples of this. Volumetry measurements are of special interest after tumor resection for follow up of liver regrow. The segmentation of resected livers presents additional challenges that were not addressed by state of the art algorithms. This paper presents a snakes based algorithm specially developed for the segmentation of resected livers. The algorithm is enhanced with a novel dynamic smoothing technique that allows the activecontour to propagate with different speeds depending on the intensities visible in its neighborhood. The algorithm is evaluated in 6 clinical CT images as well as 18 artificial datasets generated from additional clinical CT images.

Fluorescence microscopy is frequently used to study two and three dimensional network structures formed by cytoskeletal polymer fibers such as actin filaments and microtubules. While these cytoskeletal structures are often dilute enough to allow imaging of individual filaments or bundles of them, quantitative analysis of these images is challenging. To facilitate quantitative, reproducible and objective analysis of the image data, we developed a semi-automated method to extract actin networks and retrieve their topology in 3D. Our method uses multiple Stretching Open ActiveContours (SOACs) that are automatically initialized at image intensity ridges and then evolve along the centerlines of filaments in the network. SOACs can merge, stop at junctions, and reconfigure with others to allow smooth crossing at junctions of filaments. The proposed approach is generally applicable to images of curvilinear networks with low SNR. We demonstrate its potential by extracting the centerlines of synthetic meshwork images, actin networks in 2D TIRF Microscopy images, and 3D actin cable meshworks of live fission yeast cells imaged by spinning disk confocal microscopy.

Purpose: To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an activecontourmodel with interpolated respiration learned from diaphragm motion. Methods: Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered with the CBCT projections on the frame-by-frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An activecontour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy. Results: The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain. Conclusion: The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.

Purpose: To develop a novel strategy to extract the lung tumor motion from cone beam CT (CBCT) projections by an activecontourmodel with interpolated respiration learned from diaphragm motion. Methods: Tumor tracking on CBCT projections was accomplished with the templates derived from planning CT (pCT). There are three major steps in the proposed algorithm: 1) The pCT was modified to form two CT sets: a tumor removed pCT and a tumor only pCT, the respective digitally reconstructed radiographs DRRtr and DRRto following the same geometry of the CBCT projections were generated correspondingly. 2) The DRRtr was rigidly registered with the CBCT projections on the frame-by-frame basis. Difference images between CBCT projections and the registered DRRtr were generated where the tumor visibility was appreciably enhanced. 3) An activecontour method was applied to track the tumor motion on the tumor enhanced projections with DRRto as templates to initialize the tumor tracking while the respiratory motion was compensated for by interpolating the diaphragm motion estimated by our novel constrained linear regression approach. CBCT and pCT from five patients undergoing stereotactic body radiotherapy were included in addition to scans from a Quasar phantom programmed with known motion. Manual tumor tracking was performed on CBCT projections and was compared to the automatic tracking to evaluate the algorithm accuracy. Results: The phantom study showed that the error between the automatic tracking and the ground truth was within 0.2mm. For the patients the discrepancy between the calculation and the manual tracking was between 1.4 and 2.2 mm depending on the location and shape of the lung tumor. Similar patterns were observed in the frequency domain. Conclusion: The new algorithm demonstrated the feasibility to track the lung tumor from noisy CBCT projections, providing a potential solution to better motion management for lung radiation therapy.

Graph cuts and activecontours are two very popular interactive object segmentation techniques in the field of computer vision and image processing. However, both these approaches have their own well-known limitations. Graph cut methods perform efficiently giving global optimal segmentation result for smaller images. However, for larger images, huge graphs need to be constructed which not only takes an unacceptable amount of memory but also increases the time required for segmentation to a great extent. On the other hand, in case of activecontours, initial contour selection plays an important role in the accuracy of the segmentation. So a proper selection of initial contour may improve the complexity as well as the accuracy of the result. In this paper, we have tried to combine these two approaches to overcome their above-mentioned drawbacks and develop a fast technique of object segmentation. Here, we have used a pyramidal framework and applied the mincut/maxflow algorithm on the lowest resolution image with the least number of seed points possible which will be very fast due to the smaller size of the image. Then, the obtained segmentation contour is super-sampled and and worked as the initial contour for the next higher resolution image. As the initial contour is very close to the actual contour, so fewer number of iterations will be required for the convergence of the contour. The process is repeated for all the high-resolution images and experimental results show that our approach is faster as well as memory efficient as compare to both graph cut or activecontour segmentation alone.

Full Text Available We propose a 3-step algorithm for the automatic detection of moving objects in video sequences using region-based activecontours. First, we introduce a very full general framework for region-based activecontours with a new Eulerian method to compute the evolution equation of the activecontour from a criterion including both region-based and boundary-based terms. This framework can be easily adapted to various applications, thanks to the introduction of functions named descriptors of the different regions. With this new Eulerian method based on shape optimization principles, we can easily take into account the case of descriptors depending upon features globally attached to the regions. Second, we propose a 3-step algorithm for detection of moving objects, with a static or a mobile camera, using region-based activecontours. The basic idea is to hierarchically associate temporal and spatial information. The activecontour evolves with successively three sets of descriptors: a temporal one, and then two spatial ones. The third spatial descriptor takes advantage of the segmentation of the image in intensity homogeneous regions. User interaction is reduced to the choice of a few parameters at the beginning of the process. Some experimental results are supplied.

Purpose: To develop a new approach for interobserver variability analysis. Methods and Materials: Eight radiation oncologists specializing in breast cancer radiation therapy delineated a patient's left breast “from scratch” and from a template that was generated using deformable image registration. Three of the radiation oncologists had previously received training in Radiation Therapy Oncology Group consensus contouring for breast cancer atlas. The simultaneous truth and performance level estimation algorithm was applied to the 8 contours delineated “from scratch” to produce a group consensus contour. Individual Jaccard scores were fitted to a beta distribution model. We also applied this analysis to 2 or more patients, which were contoured by 9 breast radiation oncologists from 8 institutions. Results: The beta distribution model had a mean of 86.2%, standard deviation (SD) of ±5.9%, a skewness of −0.7, and excess kurtosis of 0.55, exemplifying broad interobserver variability. The 3 RTOG-trained physicians had higher agreement scores than average, indicating that their contours were close to the group consensus contour. One physician had high sensitivity but lower specificity than the others, which implies that this physician tended to contour a structure larger than those of the others. Two other physicians had low sensitivity but specificity similar to the others, which implies that they tended to contour a structure smaller than the others. With this information, they could adjust their contouring practice to be more consistent with others if desired. When contouring from the template, the beta distribution model had a mean of 92.3%, SD ± 3.4%, skewness of −0.79, and excess kurtosis of 0.83, which indicated a much better consistency among individual contours. Similar results were obtained for the analysis of 2 additional patients. Conclusions: The proposed statistical approach was able to measure interobserver variability quantitatively

We present a computerized method for the semi-automatic detection of contours in ultrasound images. The novelty of our study is the introduction of a fast and efficient image function relating to parametric activecontourmodels. This new function is a combination of the gray-level information and first-order statistical features, called standard deviation parameters. In a comprehensive study, the developed algorithm and the efficiency of segmentation were first tested for synthetic images. Tests were also performed on breast and liver ultrasound images. The proposed method was compared with the watershed approach to show its efficiency. The performance of the segmentation was estimated using the area error rate. Using the standard deviation textural feature and a 5×5 kernel, our curve evolution was able to produce results close to the minimal area error rate (namely 8.88% for breast images and 10.82% for liver images). The image resolution was evaluated using the contrast-to-gradient method. The experiments showed promising segmentation results.

Full Text Available This paper presents a novel activecontourmodel in a variational level set formulation for simultaneous segmentation and bias field estimation of medical images. An energy function is formulated based on improved Kullback-Leibler distance (KLD with likelihood ratio. According to the additive model of images with intensity inhomogeneity, we characterize the statistics of image intensities belonging to each different object in local regions as Gaussian distributions with different means and variances. Then, we use the Gaussian distribution with bias field as a local region descriptor in level set formulation for segmentation and bias field correction of the images with inhomogeneous intensities. Therefore, image segmentation and bias field estimation are simultaneously achieved by minimizing the level set formulation. Experimental results demonstrate desirable performance of the proposed method for different medical images with weak boundaries and noise.

Full Text Available Building roof contours are considered as very important geometric data, which have been widely applied in many fields, including but not limited to urban planning, land investigation, change detection and military reconnaissance. Currently, the demand on building contours at a finer scale (especially in urban areas has been raised in a growing number of studies such as urban environment quality assessment, urban sprawl monitoring and urban air pollution modelling. LiDAR is known as an effective means of acquiring 3D roof points with high elevation accuracy. However, the precision of the building contour obtained from LiDAR data is restricted by its relatively low scanning resolution. With the use of the texture information from high-resolution imagery, the precision can be improved. In this study, an improved snake model is proposed to refine the initial building contours extracted from LiDAR. First, an improved snake model is constructed with the constraints of the deviation angle, image gradient, and area. Then, the nodes of the contour are moved in a certain range to find the best optimized result using greedy algorithm. Considering both precision and efficiency, the candidate shift positions of the contour nodes are constrained, and the searching strategy for the candidate nodes is explicitly designed. The experiments on three datasets indicate that the proposed method for building contour refinement is effective and feasible. The average quality index is improved from 91.66% to 93.34%. The statistics of the evaluation results for every single building demonstrated that 77.0% of the total number of contours is updated with higher quality index.

Activecontours are a popular method for extraction of object boundaries in medical images. However, they may fail to give correct results if there are other edges in the neighbourhood. To handle and even exploit a geometrical relation between neighbouring boundaries, we propose to use a set of

Ultrasound imaging is an effective approach for diagnosing breast cancer, but it is highly operator-dependent. Recent advances in computer-aided diagnosis have suggested that it can assist physicians in diagnosis. Definition of the region of interest before computer analysis is still needed. Since manual outlining of the tumor contour is tedious and time-consuming for a physician, developing an automatic segmentation method is important for clinical application. The present paper represents a novel method to segment breast ultrasound images. It utilizes a combination of region-based activecontour and neutrosophic theory to overcome the natural properties of ultrasound images including speckle noise and tissue-related textures. First, due to inherent speckle noise and low contrast of these images, we have utilized a non-local means filter and fuzzy logic method for denoising and image enhancement, respectively. This paper presents an improved weighted region-scalable activecontour to segment breast ultrasound images using a new feature derived from neutrosophic theory. This method has been applied to 36 breast ultrasound images. It generates true-positive and false-positive results, and similarity of 95%, 6%, and 90%, respectively. The purposed method indicates clear advantages over other conventional methods of activecontour segmentation, i.e., region-scalable fitting energy and weighted region-scalable fitting energy.

We propose an unsupervised statistical region based activecontour approach integrating an original fractional entropy measure for image segmentation with a particular application to single channel actin tagged fluorescence confocal microscopy image segmentation. Following description of statistical based activecontour segmentation and the mathematical definition of the proposed fractional entropy descriptor, we demonstrate comparative segmentation results between the proposed approach and s...

Federal Emergency Management Agency, Department of Homeland Security — This layer contains contours that were derived from the digital terrain model made up of irregularly spaced mass points and breaklines. The contours are 5 foot...

Visual illusions and perceptual grouping phenomena offer an invaluable tool for probing the computational mechanism of low-level visual processing. Some illusions, like the Kanizsa figure, reveal illusory contours that form edges collinear with the inducing stimulus. This kind of illusory contour has been modeled by neural network models by way of cells equipped with elongated spatial receptive fields designed to detect and complete the collinear alignment. There are, however, other illusory groupings which are not so easy to account for in neural network terms. The Ehrenstein illusion exhibits an illusory contour that forms a contour orthogonal to the stimulus instead of collinear with it. Other perceptual grouping effects reveal illusory contours that exhibit a sharp corner or vertex, and still others take the form of vertices defined by the intersection of three, four, or more illusory contours that meet at a point. A direct extension of the collinear completion models to account for these phenomena tends towards a combinatorial explosion, because it would suggest cells with specialized receptive fields configured to perform each of those completion types, each of which would have to be replicated at every location and every orientation across the visual field. These phenomena therefore challenge the adequacy of the neural network approach to account for these diverse perceptual phenomena. I have proposed elsewhere an alternative paradigm of neurocomputation in the harmonic resonance theory (Lehar 1999, see website), whereby pattern recognition and completion are performed by spatial standing waves across the neural substrate. The standing waves perform a computational function analogous to that of the spatial receptive fields of the neural network approach, except that, unlike that paradigm, a single resonance mechanism performs a function equivalent to a whole array of spatial receptive fields of different spatial configurations and of different orientations

This paper proposes a new activecontourmodel (ACM), called ACM Crisp, and evaluates the segmentation of lungs in computed tomography (CT) images. An ACM draws a curve around or within the object of interest. This curve changes its shape, when some energy acts on it and moves towards the edges of the object. This process is performed by successive iterations of minimization of a given energy, associated with the curve. The ACMs described in the literature have limitations when used for segmentations of CT lung images. The ACM Crisp model overcomes these limitations, since it proposes automatic initiation and new external energy based on rules and radiological pulmonary densities. The paper compares other ACMs with the proposed method, which is shown to be superior. In order to validate the algorithm a medical expert in the field of Pulmonology of the Walter Cantidio University Hospital from the Federal University of Ceara carried out a qualitative analysis. In these analyses 100 CT lung images were used. The segmentation efficiency was evaluated into 5 categories with the following results for the ACM Crisp: 73% excellent, without errors, 20% acceptable, with small errors, and 7% reasonable, with large errors, 0% poor, covering only a small part of the lung, and 0% very bad, making a totally incorrect segmentation. In conclusion the ACM Crisp is considered a useful algorithm to segment CT lung images, and with potential to integrate medical diagnosis systems. (author)

We explored how contour information in primary visual cortex might be embedded in the simultaneous activity of multiple cells recorded with a 100-electrode array. Synchronous activity in cat visual cortex was more selective and predictable in discriminating between drifting grating and concentric ring stimuli than changes in firing rate. Synchrony was found even between cells with wholly different orientation preferences when their receptive fields were circularly aligned, and membership in synchronous groups was orientation and curvature dependent. The existence of synchrony between cocircular cells reinforces its role as a general mechanism for contour integration and shape detection as predicted by association field concepts. Our data suggest that cortical synchrony results from common and synchronous input from earlier visual areas and that it could serve to shape extrastriate response selectivity.

Our purpose is to develop a fully automated scheme for liver volume measurement in abdominal MR images, without requiring any user input or interaction. The proposed scheme is fully automatic for liver volumetry from 3D abdominal MR images, and it consists of three main stages: preprocessing, rough liver shape generation, and liver extraction. The preprocessing stage reduced noise and enhanced the liver boundaries in 3D abdominal MR images. The rough liver shape was revealed fully automatically by using the watershed segmentation, thresholding transform, morphological operations, and statistical properties of the liver. An activecontourmodel was applied to refine the rough liver shape to precisely obtain the liver boundaries. The liver volumes calculated by the proposed scheme were compared to the "gold standard" references which were estimated by an expert abdominal radiologist. The liver volumes computed by using our developed scheme excellently agreed (Intra-class correlation coefficient was 0.94) with the "gold standard" manual volumes by the radiologist in the evaluation with 27 cases from multiple medical centers. The running time was 8.4 min per case on average. We developed a fully automated liver volumetry scheme in MR, which does not require any interaction by users. It was evaluated with cases from multiple medical centers. The liver volumetry performance of our developed system was comparable to that of the gold standard manual volumetry, and it saved radiologists' time for manual liver volumetry of 24.7 min per case.

Visual processing of objects makes use of both feedforward and feedback streams of information. However, the nature of feedback signals is largely unknown, as is the identity of the neuronal populations in lower visual areas that receive them. Here, we develop a recurrent neural model to address these questions in the context of contour integration and figure-ground segregation. A key feature of our model is the use of grouping neurons whose activity represents tentative objects ("proto-objects") based on the integration of local feature information. Grouping neurons receive input from an organized set of local feature neurons, and project modulatory feedback to those same neurons. Additionally, inhibition at both the local feature level and the object representation level biases the interpretation of the visual scene in agreement with principles from Gestalt psychology. Our model explains several sets of neurophysiological results (Zhou et al. Journal of Neuroscience, 20(17), 6594-6611 2000; Qiu et al. Nature Neuroscience, 10(11), 1492-1499 2007; Chen et al. Neuron, 82(3), 682-694 2014), and makes testable predictions about the influence of neuronal feedback and attentional selection on neural responses across different visual areas. Our model also provides a framework for understanding how object-based attention is able to select both objects and the features associated with them.

Because of its complicated structure, low signal/noise ratio, low contrast and blurry boundaries, fully automated segmentation of a breast ultrasound (BUS) image is a difficult task. In this paper, a novel segmentation method for BUS images without human intervention is proposed. Unlike most published approaches, the proposed method handles the segmentation problem by using a two-step strategy: ROI generation and ROI segmentation. First, a well-trained texture classifier categorizes the tissues into different classes, and the background knowledge rules are used for selecting the regions of interest (ROIs) from them. Second, a novel probability distance-based activecontourmodel is applied for segmenting the ROIs and finding the accurate positions of the breast tumors. The activecontourmodel combines both global statistical information and local edge information, using a level set approach. The proposed segmentation method was performed on 103 BUS images (48 benign and 55 malignant). To validate the performance, the results were compared with the corresponding tumor regions marked by an experienced radiologist. Three error metrics, true-positive ratio (TP), false-negative ratio (FN) and false-positive ratio (FP) were used for measuring the performance of the proposed method. The final results (TP = 91.31%, FN = 8.69% and FP = 7.26%) demonstrate that the proposed method can segment BUS images efficiently, quickly and automatically.

GIS (Geographical Information System) is one of the most striking innovation for mapping applications supplied by the developing computer and software technology to users. GIS is a very effective tool which can show visually combination of the geographical and non-geographical data by recording these to allow interpretations and analysis. DEM (Digital Elevation Model) is an inalienable component of the GIS. The existing TM (Topographic Map) can be used as the main data source for generating DEM by amanual digitizing or vectorization process for the contours polylines. The aim of this study is to examine the DEM accuracies, which were obtained by TMs, as depending on the number of sampling points and grid size. For these purposes, the contours of the several 1/1000 scaled scanned topographical maps were vectorized. The different DEMs of relevant area have been created by using several datasets with different numbers of sampling points. We focused on the DEM creation from contour lines using gridding with RBF (Radial Basis Function) interpolation techniques, namely TPS as the surface fitting model. The solution algorithm and a short review of the mathematical model of TPS (Thin Plate Spline) interpolation techniques are given. In the test study, results of the application and the obtained accuracies are drawn and discussed. The initial object of this research is to discuss the requirement of DEM in GIS, urban planning, surveying engineering and the other applications with high accuracy (a few deci meters). (author)

Transfer functions facilitate the volumetric data visualization by assigning optical properties to various data features and scalar values. Automation of transfer function specifications still remains a challenge in volume rendering. This paper presents an approach for automating transfer function generations by utilizing topological attributes derived from the contour tree of a volume. The contour tree acts as a visual index to volume segments, and captures associated topological attributes involved in volumetric data. A residue flow model based on Darcy's Law is employed to control distributions of opacity between branches of the contour tree. Topological attributes are also used to control color selection in a perceptual color space and create harmonic color transfer functions. The generated transfer functions can depict inclusion relationship between structures and maximize opacity and color differences between them. The proposed approach allows efficient automation of transfer function generations, and exploration on the data to be carried out based on controlling of opacity residue flow rate instead of complex low-level transfer function parameter adjustments. Experiments on various data sets demonstrate the practical use of our approach in transfer function generations.

We are developing a computer-aided diagnosis (CAD) system to classify malignant and benign lung nodules found on CT scans. A fully automated system was designed to segment the nodule from its surrounding structured background in a local volume of interest (VOI) and to extract image features for classification. Image segmentation was performed with a three-dimensional (3D) activecontour (AC) method. A data set of 96 lung nodules (44 malignant, 52 benign) from 58 patients was used in this study. The 3D AC model is based on two-dimensional AC with the addition of three new energy components to take advantage of 3D information: (1) 3D gradient, which guides the activecontour to seek the object surface (2) 3D curvature, which imposes a smoothness constraint in the z direction, and (3) mask energy, which penalizes contours that grow beyond the pleura or thoracic wall. The search for the best energy weights in the 3D AC model was guided by a simplex optimization method. Morphological and gray-level features were extracted from the segmented nodule. The rubber band straightening transform (RBST) was applied to the shell of voxels surrounding the nodule. Texture features based on run-length statistics were extracted from the RBST image. A linear discriminant analysis classifier with stepwise feature selection was designed using a second simplex optimization to select the most effective features. Leave-one-case-out resampling was used to train and test the CAD system. The system achieved a test area under the receiver operating characteristic curve (A z ) of 0.83±0.04. Our preliminary results indicate that use of the 3D AC model and the 3D texture features surrounding the nodule is a promising approach to the segmentation and classification of lung nodules with CAD. The segmentation performance of the 3D AC model trained with our data set was evaluated with 23 nodules available in the Lung Image Database Consortium (LIDC). The lung nodule volumes segmented by the 3D AC

Full Text Available This paper deals with video segmentation for MPEG-4 and MPEG-7 applications. Region-based activecontour is a powerful technique for segmentation. However most of these methods are implemented using level sets. Although level-set methods provide accurate segmentation, they suffer from large computational cost. We propose to use a regular B-spline parametric method to provide a fast and accurate segmentation. Our B-spline interpolation is based on a fixed number of points 2j depending on the level of the desired details. Through this spatial multiresolution approach, the computational cost of the segmentation is reduced. We introduce a length penalty. This results in improving both smoothness and accuracy. Then we show some experiments on real-video sequences.

Detecting the shape of the non-rigid molten metal during welding, so-called weld pool visual sensing, is one of the central tasks for automating arc welding processes. It is challenging due to the strong interference of the high-intensity arc light and spatters as well as the lack of robust...... approaches to detect and represent the shape of the nonrigid weld pool. We propose a solution using activecontours including an prior for the weld pool boundary composition. Also, we apply Adaboost to select a small set of features that captures the relevant information. The proposed method is applied...... to weld pool tracking and the presented results verified its feasibility....

Purpose: To use feed-forward activecontours (snakes) to track and measure brachial artery vasomotion on ultrasound images recorded in both transverse and longitudinal views; and to compare the algorithm's performance in each view. Methods: Longitudinal and transverse view ultrasound image sequences of 45 brachial arteries were segmented by feed-forward activecontour (FFAC). The segmented regions were used to measure vasomotion artery diameter, cross-sectional area, and distention both as peak-to-peak diameter and as area. ECG waveforms were also simultaneously extracted frame-by-frame by thresholding a running finite-difference image between consecutive images. The arterial and ECG waveforms were compared as they traced each phase of the cardiac cycle. Results: FFAC successfully segmented arteries in longitudinal and transverse views in all 45 cases. The automated analysis took significantly less time than manual tracing, but produced superior, well-behaved arterial waveforms. Automated arterial measurements also had lower interobserver variability as measured by correlation, difference in mean values, and coefficient of variation. Although FFAC successfully segmented both the longitudinal and transverse images, transverse measurements were less variable. The cross-sectional area computed from the longitudinal images was 27% lower than the area measured from transverse images, possibly due to the compression of the artery along the image depth by transducer pressure. Conclusions: FFAC is a robust and sensitive vasomotion segmentation algorithm in both transverse and longitudinal views. Transverse imaging may offer advantages over longitudinal imaging: transverse measurements are more consistent, possibly because the method is less sensitive to variations in transducer pressure during imaging.

Spectral embedding (SE), a graph-based manifold learning method, has previously been shown to be useful in high dimensional data classification. In this work, we present a novel SE based activecontour (SEAC) segmentation scheme and demonstrate its applications in lesion segmentation on breast dynamic contrast enhance magnetic resonance imaging (DCE-MRI). In this work, we employ SE on DCE-MRI on a per voxel basis to embed the high dimensional time series intensity vector into a reduced dimensional space, where the reduced embedding space is characterized by the principal eigenvectors. The orthogonal eigenvector-based data representation allows for computation of strong tensor gradients in the spectrally embedded space and also yields improved region statistics that serve as optimal stopping criteria for SEAC. We demonstrate both analytically and empirically that the tensor gradients in the spectrally embedded space are stronger than the corresponding gradients in the original grayscale intensity space. On a total of 50 breast DCE-MRI studies, SEAC yielded a mean absolute difference (MAD) of 3.2+/-2.1 pixels and mean Dice similarity coefficient (DSC) of 0.74+/-0.13 compared to manual ground truth segmentation. An activecontour in conjunction with fuzzy c-means (FCM+AC), a commonly used segmentation method for breast DCE-MRI, produced a corresponding MAD of 7.2+/-7.4 pixels and mean DSC of 0.58+/-0.32. In conjunction with a set of 6 quantitative morphological features automatically extracted from the SEAC derived lesion boundary, a support vector machine (SVM) classifier yielded an area under the curve (AUC) of 0.73, for discriminating between 10 benign and 30 malignant lesions; the corresponding SVM classifier with the FCM+AC derived morphological features yielded an AUC of 0.65.

Full Text Available A unified reciprocity-based modeling approach for analyzing electromagnetic fields in dispersive parallel-plane structures of arbitrary shape is described. It is shown that the use of the reciprocity theorem of the time-convolution type leads to a global contour-integral interaction quantity from which novel both time- and frequency-domain numerical schemes can be arrived at. Applications of the numerical method concerning the time-domain radiated interference and susceptibility of parallel-plane structures are discussed and illustrated on numerical examples.

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets

Purpose: One of the most critical steps in radiation therapy treatment is accurate tumor and critical organ-at-risk (OAR) contouring. Both manual and automated contouring processes are prone to errors and to a large degree of inter- and intraobserver variability. These are often due to the limitations of imaging techniques in visualizing human anatomy as well as to inherent anatomical variability among individuals. Physicians/physicists have to reverify all the radiation therapy contours of every patient before using them for treatment planning, which is tedious, laborious, and still not an error-free process. In this study, the authors developed a general strategy based on novel geometric attribute distribution (GAD) models to automatically detect radiation therapy OAR contouring errors and facilitate the current clinical workflow. Methods: Considering the radiation therapy structures’ geometric attributes (centroid, volume, and shape), the spatial relationship of neighboring structures, as well as anatomical similarity of individual contours among patients, the authors established GAD models to characterize the interstructural centroid and volume variations, and the intrastructural shape variations of each individual structure. The GAD models are scalable and deformable, and constrained by their respective principal attribute variations calculated from training sets with verified OAR contours. A new iterative weighted GAD model-fitting algorithm was developed for contouring error detection. Receiver operating characteristic (ROC) analysis was employed in a unique way to optimize the model parameters to satisfy clinical requirements. A total of forty-four head-and-neck patient cases, each of which includes nine critical OAR contours, were utilized to demonstrate the proposed strategy. Twenty-nine out of these forty-four patient cases were utilized to train the inter- and intrastructural GAD models. These training data and the remaining fifteen testing data sets

Automatic liver segmentation on CT images is challenging because the liver often abuts other organs of a similar density. Our purpose was to develop an accurate automated liver segmentation scheme for measuring liver volumes. We developed an automated volumetry scheme for the liver in CT based on a 5 step schema. First, an anisotropic smoothing filter was applied to portal-venous phase CT images to remove noise while preserving the liver structure, followed by an edge enhancer to enhance the liver boundary. By using the boundary-enhanced image as a speed function, a fastmarching algorithm generated an initial surface that roughly estimated the liver shape. A geodesic-active-contour segmentation algorithm coupled with level-set contour-evolution refined the initial surface so as to more precisely fit the liver boundary. The liver volume was calculated based on the refined liver surface. Hepatic CT scans of eighteen prospective liver donors were obtained under a liver transplant protocol with a multi-detector CT system. Automated liver volumes obtained were compared with those manually traced by a radiologist, used as "gold standard." The mean liver volume obtained with our scheme was 1,520 cc, whereas the mean manual volume was 1,486 cc, with the mean absolute difference of 104 cc (7.0%). CT liver volumetrics based on an automated scheme agreed excellently with "goldstandard" manual volumetrics (intra-class correlation coefficient was 0.95) with no statistically significant difference (p(F<=f)=0.32), and required substantially less completion time. Our automated scheme provides an efficient and accurate way of measuring liver volumes.

Morphology of individual microcalcifications is an important clinical factor in microcalcification clusters diagnosis. Accurate segmentation remains a difficult task due to microcalcifications small size, low contrast, fuzzy nature and low distinguishability from surrounding tissue. A novel application of active rays (polar transformed activecontours) on B-spline wavelet representation is employed, to provide initial estimates of microcalcification boundary. Then, a region growing method is used with pixel aggregation constrained by the microcalcification boundary estimates, to obtain the final microcalcification boundary. The method was tested on dataset of 49 microcalcification clusters (30 benign, 19 malignant), originating from the DDSM database. An observer study was conducted to evaluate segmentation accuracy of the proposed method, on a 5-point rating scale (from 5:excellent to 1:very poor). The average accuracy rating was 3.98±0.81 when multiscale active rays were combined to region growing and 2.93±0.92 when combined to linear polynomial fitting, while the difference in rating of segmentation accuracy was statistically significant (p < 0.05).

In emission imaging, nuclear medicine provides functional information about the organ of interest. In transmission imaging, it provides anatomical information whose goal may be the correction of physical phenomena that corrupt emission images. With both emission and transmission images, it is useful to know how to extract, either automatically or semi-automatically, the organs of interest and the body outline in the case of a large field of view. This is the aim of segmentation. We developed two activecontour segmentation methods. They were implemented using level sets. The key point is the evolution velocity definition. First, we were interested in static transmission imaging of the thorax. The evolution velocity was heuristically defined and depended only on the acquired projections. The segmented transmission map was computed w/o reconstruction and could be advantageously used for attenuation correction. Then, we studied the segmentation of cardiac gated sequences. The developed space-time segmentation method results from the minimization of a variational criterion which takes into account the whole sequence. The computed segmentation could be used for calculating physiological parameters. As an illustration, we computed the ejection fraction. Finally, we exploited some level set properties to develop a non-rigid, non-parametric, and geometric registration method. We applied it for kinetic compensation of cardiac gated sequences. The registered images were then added together providing an image with noise characteristics similar to a cardiac static image but w/o motion-induced blurring. (author)

Our purpose was to develop an accurate automated 3D liver segmentation scheme for measuring liver volumes on MRI. Our scheme for MRI liver volumetry consisted of three main stages. First, the preprocessing stage was applied to T1-weighted MRI of the liver in the portal venous phase to reduce noise and produce the boundary-enhanced image. This boundary-enhanced image was used as a speed function for a 3D fast-marching algorithm to generate an initial surface that roughly approximated the shape of the liver. A 3D geodesic-active-contour segmentation algorithm refined the initial surface to precisely determine the liver boundaries. The liver volumes determined by our scheme were compared with those manually traced by a radiologist, used as the reference standard. The two volumetric methods reached excellent agreement (intraclass correlation coefficient, 0.98) without statistical significance (p = 0.42). The average (± SD) accuracy was 99.4% ± 0.14%, and the average Dice overlap coefficient was 93.6% ± 1.7%. The mean processing time for our automated scheme was 1.03 ± 0.13 minutes, whereas that for manual volumetry was 24.0 ± 4.4 minutes (p volumetry based on our automated scheme agreed excellently with reference-standard volumetry, and it required substantially less completion time.

that uses region-scalable discriminant and fitting energy functional for handling the intensity inhomogeneity and weak boundary problems in medical image segmentation. The region-scalable discriminant and fitting energy functional is defined to capture the image intensity characteristics in local and global regions for driving the evolution of activecontour. The discriminant term in the model aims at separating background and foreground in scalable regions while the fitting term tends to fit the intensity in these regions. This model is then transformed into a variational level set formulation with a level set regularization term for accurate computation. The new model utilizes intensity information in the local and global regions as much as possible; so it not only handles better intensity inhomogeneity, but also allows more robustness to noise and more flexible initialization in comparison to the original global region and regional-scalable based models. Experimental results for synthetic and real medical image segmentation show the advantages of the proposed method in terms of accuracy and robustness.

Bone age assessment (BAA) is a task performed on radiographs by the pediatricians in hospitals to predict the final adult height, to diagnose growth disorders by monitoring skeletal development. For building an automatic bone age assessment system the step in routine is to do image pre-processing of the bone X-rays so that features row can be constructed. In this research paper, an enhanced point distribution algorithm using contours has been implemented for segmenting bone parts as per well-established procedure of bone age assessment that would be helpful in building feature row and later on; it would be helpful in construction of automatic bone age assessment system. Implementation of the segmentation algorithm shows high degree of accuracy in terms of recall and precision in segmenting bone parts from left hand X-Rays.

Full Text Available Analysis and synthesis of mechanisms is one of the fundamental tasks of engineering. Mechanisms can suffer from errors due to versatile reasons. Graph-based methods of analysis and synthesis of planetary gears constitute an alternative method for checking their correctness. Previous applications of the graph theory concerned modelling gears for dynamic analysis, kinematic analysis, synthesis, structural analysis, gearshift optimization and automatic design based on so-called graph grammars. Some tasks may be performed only with the methods resulting from the graph theory, e.g. enumeration of structural solutions. The contour plot method consists in distinguishing a series of consecutive rigid units of the analysed mechanism, forming a closed loop (so-called contour. At a later stage, it is possible to analyze the obtained contour graph as a directed graph of dependence. This work presents an example of the application of game-tree structures in describing the contour graph of a planetary gear. In addition, complex parametric tree structures are included.

The purpose of this study is to investigate the effects of CT scanning and reconstruction parameters on automated segmentation and volumetric measurements of nodules in CT images. Phantom nodules of known sizes were used so that segmentation accuracy could be quantified in comparison to ground-truth volumes. Spherical nodules having 4.8, 9.5 and 16 mm diameters and 50 and 100 mg cc -1 calcium contents were embedded in lung-tissue-simulating foam which was inserted in the thoracic cavity of a chest section phantom. CT scans of the phantom were acquired with a 16-slice scanner at various tube currents, pitches, fields-of-view and slice thicknesses. Scans were also taken using identical techniques either within the same day or five months apart for study of reproducibility. The phantom nodules were segmented with a three-dimensional activecontour (3DAC) model that we previously developed for use on patient nodules. The percentage volume errors relative to the ground-truth volumes were estimated under the various imaging conditions. There was no statistically significant difference in volume error for repeated CT scans or scans taken with techniques where only pitch, field of view, or tube current (mA) were changed. However, the slice thickness significantly (p < 0.05) affected the volume error. Therefore, to evaluate nodule growth, consistent imaging conditions and high resolution should be used for acquisition of the serial CT scans, especially for smaller nodules. Understanding the effects of scanning and reconstruction parameters on volume measurements by 3DAC allows better interpretation of data and assessment of growth. Tracking nodule growth with computerized segmentation methods would reduce inter- and intraobserver variabilities

Activecontourmodel (ACM) plays an important role in computer vision and medical image application. The traditional ACMs were used to extract single-class of object contours. While, simultaneous extraction of multi-class of interesting contours (i.e., various contours with closed- or open-ended) have not been solved so far. Therefore, a novel ACM model named “Ingenious Snake” is proposed to adaptively extract these interesting contours. In the first place, the ridge-points are extracted based on the local phase measurement of gradient vector flow field; the consequential ridgelines initialization are automated with high speed. Secondly, the contours’ deformation and evolvement are implemented with the ingenious snake. In the experiments, the result from initialization, deformation and evolvement are compared with the existing methods. The quantitative evaluation of the structure extraction is satisfying with respect of effectiveness and accuracy.

Purpose: This study aims to develop a tool to rapidly delineate cardiac substructures for use in dosimetry for large-scale clinical trial or epidemiological investigations. The goal is to produce a system that can semi-automatically delineate nine cardiac structures to a reasonable accuracy within a couple of minutes. Methods: The cardiac contouring tool employs a Most Similar Atlas method, where a selection criterion is used to pre-select the most similar model to the patient from a library of pre-defined atlases. Sixty contrast-enhanced cardiac computed tomography angiography (CTA) scans (30 male and 30 female) were manually contoured to serve as the atlas library. For each CTA 12 structures were delineated. Kabsch algorithm was used to compute the optimum rotation and translation matrices between the patient and atlas. Minimum root mean squared distance between the patient and atlas after transformation was used to select the most-similar atlas. An initial study using 10 CTA sets was performed to assess system feasibility. Leave-one patient out method was performed, and fit criteria were calculated to evaluate the fit accuracy compared to manual contours. Results: For the pilot study, mean dice indices of .895 were achieved for the whole heart, .867 for the ventricles, and .802 for the atria. In addition, mean distance was measured via the chord length distribution (CLD) between ground truth and the atlas structures for the four coronary arteries. The mean CLD for all coronary arteries was below 14mm, with the left circumflex artery showing the best agreement (7.08mm). Conclusion: The cardiac contouring tool is able to delineate cardiac structures with reasonable accuracy in less than 90 seconds. Pilot data indicates that the system is able to delineate the whole heart and ventricles within a reasonable accuracy using even a limited library. We are extending the atlas sets to 60 adult males and females in total.

Purpose: This study aims to develop a tool to rapidly delineate cardiac substructures for use in dosimetry for large-scale clinical trial or epidemiological investigations. The goal is to produce a system that can semi-automatically delineate nine cardiac structures to a reasonable accuracy within a couple of minutes. Methods: The cardiac contouring tool employs a Most Similar Atlas method, where a selection criterion is used to pre-select the most similar model to the patient from a library of pre-defined atlases. Sixty contrast-enhanced cardiac computed tomography angiography (CTA) scans (30 male and 30 female) were manually contoured to serve as the atlas library. For each CTA 12 structures were delineated. Kabsch algorithm was used to compute the optimum rotation and translation matrices between the patient and atlas. Minimum root mean squared distance between the patient and atlas after transformation was used to select the most-similar atlas. An initial study using 10 CTA sets was performed to assess system feasibility. Leave-one patient out method was performed, and fit criteria were calculated to evaluate the fit accuracy compared to manual contours. Results: For the pilot study, mean dice indices of .895 were achieved for the whole heart, .867 for the ventricles, and .802 for the atria. In addition, mean distance was measured via the chord length distribution (CLD) between ground truth and the atlas structures for the four coronary arteries. The mean CLD for all coronary arteries was below 14mm, with the left circumflex artery showing the best agreement (7.08mm). Conclusion: The cardiac contouring tool is able to delineate cardiac structures with reasonable accuracy in less than 90 seconds. Pilot data indicates that the system is able to delineate the whole heart and ventricles within a reasonable accuracy using even a limited library. We are extending the atlas sets to 60 adult males and females in total.

We numerically investigate the link between the delocalization-localization transition and entanglement in a disordered long-range hopping model of spinless fermions by studying various static and dynamical quantities. This includes the inverse participation ratio, level statistics, entanglement entropy, and number fluctuations in the subsystem along with quench and wave-packet dynamics. Finite systems show delocalized, quasilocalized, and localized phases. The delocalized phase shows strong area-law violation, whereas the (quasi)localized phase adheres to (for large subsystems) the strict area law. The idea of "entanglement contour" nicely explains the violation of area law and its relationship with "fluctuation contour" reveals a signature at the transition point. The relationship between entanglement entropy and number fluctuations in the subsystem also carries signatures for the transition in the model. Results from the Aubry-Andre-Harper model are compared in this context. The propagation of charge and entanglement are contrasted by studying quench and wave-packet dynamics at the single-particle and many-particle levels.

Full Text Available Can lateral connectivity in the primary visual cortex account for the time dependence and intrinsic task difficulty of human contour detection? To answer this question, we created a synthetic image set that prevents sole reliance on either low-level visual features or high-level context for the detection of target objects. Rendered images consist of smoothly varying, globally aligned contour fragments (amoebas distributed among groups of randomly rotated fragments (clutter. The time course and accuracy of amoeba detection by humans was measured using a two-alternative forced choice protocol with self-reported confidence and variable image presentation time (20-200 ms, followed by an image mask optimized so as to interrupt visual processing. Measured psychometric functions were well fit by sigmoidal functions with exponential time constants of 30-91 ms, depending on amoeba complexity. Key aspects of the psychophysical experiments were accounted for by a computational network model, in which simulated responses across retinotopic arrays of orientation-selective elements were modulated by cortical association fields, represented as multiplicative kernels computed from the differences in pairwise edge statistics between target and distractor images. Comparing the experimental and the computational results suggests that each iteration of the lateral interactions takes at least [Formula: see text] ms of cortical processing time. Our results provide evidence that cortical association fields between orientation selective elements in early visual areas can account for important temporal and task-dependent aspects of the psychometric curves characterizing human contour perception, with the remaining discrepancies postulated to arise from the influence of higher cortical areas.

Segmentation of breast lesions on dynamic contrast enhanced (DCE) magnetic resonance imaging (MRI) is the first step in lesion diagnosis in a computer-aided diagnosis framework. Because manual segmentation of such lesions is both time consuming and highly susceptible to human error and issues of reproducibility, an automated lesion segmentation method is highly desirable. Traditional automated image segmentation methods such as boundary-based activecontour (AC) models require a strong gradient at the lesion boundary. Even when region-based terms are introduced to an AC model, grayscale image intensities often do not allow for clear definition of foreground and background region statistics. Thus, there is a need to find alternative image representations that might provide (1) strong gradients at the margin of the object of interest (OOI); and (2) larger separation between intensity distributions and region statistics for the foreground and background, which are necessary to halt evolution of the AC model upon reaching the border of the OOI. In this paper, the authors introduce a spectral embedding (SE) based AC (SEAC) for lesion segmentation on breast DCE-MRI. SE, a nonlinear dimensionality reduction scheme, is applied to the DCE time series in a voxelwise fashion to reduce several time point images to a single parametric image where every voxel is characterized by the three dominant eigenvectors. This parametric eigenvector image (PrEIm) representation allows for better capture of image region statistics and stronger gradients for use with a hybrid AC model, which is driven by both boundary and region information. They compare SEAC to ACs that employ fuzzy c-means (FCM) and principal component analysis (PCA) as alternative image representations. Segmentation performance was evaluated by boundary and region metrics as well as comparing lesion classification using morphological features from SEAC, PCA+AC, and FCM+AC. On a cohort of 50 breast DCE-MRI studies, Pr

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE's. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

Following the seminal work of Nesterov, accelerated optimization methods have been used to powerfully boost the performance of first-order, gradient-based parameter estimation in scenarios where second-order optimization strategies are either inapplicable or impractical. Not only does accelerated gradient descent converge considerably faster than traditional gradient descent, but it also performs a more robust local search of the parameter space by initially overshooting and then oscillating back as it settles into a final configuration, thereby selecting only local minimizers with a basis of attraction large enough to contain the initial overshoot. This behavior has made accelerated and stochastic gradient search methods particularly popular within the machine learning community. In their recent PNAS 2016 paper, Wibisono, Wilson, and Jordan demonstrate how a broad class of accelerated schemes can be cast in a variational framework formulated around the Bregman divergence, leading to continuum limit ODE\\'s. We show how their formulation may be further extended to infinite dimension manifolds (starting here with the geometric space of curves and surfaces) by substituting the Bregman divergence with inner products on the tangent space and explicitly introducing a distributed mass model which evolves in conjunction with the object of interest during the optimization process. The co-evolving mass model, which is introduced purely for the sake of endowing the optimization with helpful dynamics, also links the resulting class of accelerated PDE based optimization schemes to fluid dynamical formulations of optimal mass transport.

Full Text Available Methods described by partial differential equations have gained a considerable interest because of undoubtful advantages such as an easy mathematical description of the underlying physics phenomena, subpixel precision, isotropy, or direct extension to higher dimensions. Though their implementation within the level set framework offers other interesting advantages, their vast industrial deployment on embedded systems is slowed down by their considerable computational effort. This paper exploits the high parallelization potential of the operators from the level set framework and proposes a scalable, asynchronous, multiprocessor platform suitable for system-on-chip solutions. We concentrate on obtaining real-time execution capabilities. The performance is evaluated on a continuous watershed and an object-tracking application based on a simple gradient-based attraction force driving the active countour. The proposed architecture can be realized on commercially available FPGAs. It is built around general-purpose processor cores, and can run code developed with usual tools.

National Oceanic and Atmospheric Administration, Department of Commerce — Ocean sediment thickness contours in 200 meter intervals for water depths ranging from 0 - 18,000 meters. These contours were derived from a global sediment...

Kansas Data Access and Support Center — The Kansas Tagged Vector Contour (TVC) dataset consists of digitized contours from the 7.5 minute topographic quadrangle maps. Coverage for the state is incomplete....

Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic activecontour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic activecontour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F{<=}f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less

Purpose: Computerized liver extraction from hepatic CT images is challenging because the liver often abuts other organs of a similar density. The purpose of this study was to develop a computer-aided measurement of liver volumes in hepatic CT. Methods: The authors developed a computerized liver extraction scheme based on geodesic activecontour segmentation coupled with level-set contour evolution. First, an anisotropic diffusion filter was applied to portal-venous-phase CT images for noise reduction while preserving the liver structure, followed by a scale-specific gradient magnitude filter to enhance the liver boundaries. Then, a nonlinear grayscale converter enhanced the contrast of the liver parenchyma. By using the liver-parenchyma-enhanced image as a speed function, a fast-marching level-set algorithm generated an initial contour that roughly estimated the liver shape. A geodesic activecontour segmentation algorithm coupled with level-set contour evolution refined the initial contour to define the liver boundaries more precisely. The liver volume was then calculated using these refined boundaries. Hepatic CT scans of 15 prospective liver donors were obtained under a liver transplant protocol with a multidetector CT system. The liver volumes extracted by the computerized scheme were compared to those traced manually by a radiologist, used as ''gold standard.''Results: The mean liver volume obtained with our scheme was 1504 cc, whereas the mean gold standard manual volume was 1457 cc, resulting in a mean absolute difference of 105 cc (7.2%). The computer-estimated liver volumetrics agreed excellently with the gold-standard manual volumetrics (intraclass correlation coefficient was 0.95) with no statistically significant difference (F=0.77; p(F≤f)=0.32). The average accuracy, sensitivity, specificity, and percent volume error were 98.4%, 91.1%, 99.1%, and 7.2%, respectively. Computerized CT liver volumetry would require substantially less completion time

The analysis of the pure motion of subnuclear structures without influence of the cell nucleus motion and deformation is essential in live cell imaging. In this paper, we propose a 2-D contour-based image registration approach for compensation of nucleus motion and deformation in fluorescence microscopy time-lapse sequences. The proposed approach extends our previous approach, which uses a static elasticity model to register cell images. Compared with that scheme, the new approach employs a dynamic elasticity model for the forward simulation of nucleus motion and deformation based on the motion of its contours. The contour matching process is embedded as a constraint into the system of equations describing the elastic behavior of the nucleus. This results in better performance in terms of the registration accuracy. Our approach was successfully applied to real live cell microscopy image sequences of different types of cells including image data that was specifically designed and acquired for evaluation of cell image registration methods. An experimental comparison with the existing contour-based registration methods and an intensity-based registration method has been performed. We also studied the dependence of the results on the choice of method parameters.

Automatic suspected lesion extraction is an important application in computer-aided diagnosis (CAD). In this paper, we propose a method to automatically extract the suspected parotid regions for clinical evaluation in head and neck CT images. The suspected lesion tissues in low contrast tissue regions can be localized with feature-based segmentation (FBS) based on local texture features, and can be delineated with accuracy by modified activecontourmodels (ACM). At first, stationary wavelet transform (SWT) is introduced. The derived wavelet coefficients are applied to derive the local features for FBS, and to generate enhanced energy maps for ACM computation. Geometric shape features (GSFs) are proposed to analyze each soft tissue region segmented by FBS; the regions with higher similarity GSFs with the lesions are extracted and the information is also applied as the initial conditions for fine delineation computation. Consequently, the suspected lesions can be automatically localized and accurately delineated for aiding clinical diagnosis. The performance of the proposed method is evaluated by comparing with the results outlined by clinical experts. The experiments on 20 pathological CT data sets show that the true-positive (TP) rate on recognizing parotid lesions is about 94%, and the dimension accuracy of delineation results can also approach over 93%.

Full Text Available Little attention had been given to the evaluation of subsectional cooling control ability under complicated working conditions. In this paper, heat generation was calculated by using finite difference method. Strip hardening, work roll elastic deformation and elastic recovery of strip were taken into account. The mean coefficient of convective heat transfer on work roll surface was simulated by FLUENT. Calculation model had used the alternative finite difference scheme, which improved the model stability and computing speed. The simulation result shows that subsectional cooling control ability is different between different rolling passes. Positive and negative control abilities are roughly the same in the same pass. The increase of rolled length, working pressure of header and friction coefficient has positive effect on subsectional cooling control ability, and the rolling speed is on the contrary. On the beginning of the pass, when work roll surface has not reached the stable temperature, control ability of subsectional cooling is mainly affected by rolled length. The effect of mean coefficient of convective heat transfer and coefficient of friction is linear. When rolling speed is over 500 m/min, control ability of subsectional cooling becomes stable.

We have created patterns in which illusory Kanizsa squares are positioned on top of a background grid of bars. When the illusory contours and physical contours are misaligned, the resulting percept appears to be rather confusing (van Lier et al, 2004 Perception 33 Supplement, 77). Observers often

Men are increasingly turning to dermatologists and plastic surgeons to request procedures that correct or enhance physical features. With the advent of this emerging new patient population, alterations in preexisting aesthetic techniques, gender-specific uses of existing devices and overall approaches need to be revisited and adapted to obtain results that are suitable for the male patient. Recently, body contouring has become one of the most sought out procedures by men. Although the majority of clinical studies involving body contouring esthetics are performed with female patients, gains from such studies can be extrapolated to men. Body contouring can be broadly classified as non-invasive or invasive, depending on the modality used. Non-invasive contouring is most frequently performed with devices that target subcutaneous adipose with focused electrical or thermal energy, including low-level laser, cryolipolysis, ultrasonography, and radiofrequency. Invasive body contouring modalities useful for male body contouring include liposuction, pectoral and abdominal wall etching, jawline fillers, synthetic deoxycholic acid injections, and solid silicone implants. The purpose of this review is to bring attention to the unique aspects, strategies, and modalities used in aesthetic body contouring for the male patient.

This paper describes a new method for interactive segmentation that is based on cross-sectional design and 3D modelling. The method represents a 3D model by a set of connected contours that are planar and orthogonal. Planar contours overlayed on image data are easily manipulated and linked contours

On 27 August, NASA Administrator Sean O'Keefe appointed a team to investigate the apparent loss of the Comet Nucleus Tour (CONTOUR) spacecraft, which stopped communicating with the mission control operations on 15 August.On that date, CONTOUR failed to communicate following the firing of its main engine that would take it out of its orbit around the Earth. Shortly afterwards, the mission team received telescope images from several observatories showing two objects traveling along the spacecraft's predicted path. Those objects could be CONTOUR, and part of the spacecraft that may have separated from it when the spacecraft's solid rocket motor fired.

We present an exponentially accurate boundary integral method for calculation the equilibria and dynamics of piece-wise constant distributions of potential vorticity. The method represents contours of potential vorticity as a spectral sum and solves the Biot-Savart equation for the velocity by spectrally evaluating a desingularized contour integral. We use the technique in both an initial-value code and a newton continuation method. Our methods are tested by comparing the numerical solutions with known analytic results, and it is shown that for the same amount of computational work our spectral methods are more accurate than other contour dynamics methods currently in use

Full Text Available Contour bank farming is a well-known agricultural management technique in areas which are characterised by intensive and erosive rainfalls. Contour banks are designed to reduce the flow velocity of overland flow and to intercept water before...

Spiral beams of light are characterized by their ability to remain structurally unchanged at propagation. They may have the shape of any closed curve. In the present paper a new approach is proposed within the framework of the contour analysis based on a close cooperation of modern coherent optics, theory of functions and numerical methods. An algorithm for comparing contours is presented and theoretically justified, which allows convincing of whether two contours are similar or not to within the scale factor and/or rotation. The advantages and disadvantages of the proposed approach are considered; the results of numerical modeling are presented.

A previous infrared multiple photon dissociation (IRMPD) action spectroscopy and density functional theory (DFT) study explored the structures of the [M,C,2H]+ products formed by dehydrogenation of methane by four, gas-phase 5d transition metal cations (M+ = Ta+, W+, Ir+, and Pt+). Complicating the analysis of these spectra for Ir and Pt was observation of an extra band in both spectra, not readily identified as a fundamental vibration. In an attempt to validate the assignment of these additional peaks, the present work examines the gas phase [M,C,2D]+ products of the same four metal ions formed by reaction with perdeuterated methane (CD4). As before, metal cations are formed in a laser ablation source and react with methane pulsed into a reaction channel downstream, and the resulting products are spectroscopically characterized through photofragmentation using the free-electron laser for intracavity experiments in the 350-1800 cm-1 range. Photofragmentation was monitored by the loss of D for [Ta,C,2D]+ and [W,C,2D]+ and of D2 in the case of [Pt,C,2D]+ and [Ir,C,2D]+. Comparison of the experimental spectra and DFT calculated spectra leads to structural assignments for all [M,C,2H/2D]+ systems that are consistent with previous identifications and allows a full description of the systematic spectroscopic shifts observed for deuterium labeling of these complexes, some of the smallest systems to be studied using IRMPD action spectroscopy. Further, full rotational contours are simulated for each vibrational band and explain several observations in the present spectra, such as doublet structures in several bands as well as the observed linewidths. The prominent extra bands in the [Pt,C,2D/2H]+ spectra appear to be most consistent with an overtone of the out-of-plane bending vibration of the metal carbene cation structure.

defined from cardiology models and agreed by two cardiologists. Reference atlas contours were delineated and written guidelines prepared. Six radiation oncologists tested the atlas. Spatial variation was assessed using the DICE similarity coefficient (DSC) and the directed Hausdorff average distance (d→H,avg......-observer contour separation (mean d→H,avg) was 1.5-2.2mm for left ventricular segments and 1.3-5.1mm for coronary artery segments. This spatial variation resulted in

Theoretical analysis and experimental results on holographic moire contouring (HMC) of difussely reflecting objects are presented. The sensitivity and application constraints of the method are discussed. A high signal-to-noise ratio and contrast of the fringes is achieved through the use of high quality silver halide holographic plates HP-650. A good agreement between theoretical and experimental results is observed.

This paper presents an approach to describing the three dimensional shape of a violin plate in mathematical form. The shape description begins with standard contour lines and ends with an equation for a surface in three dimensional space. The traditional specification of cross sectional arching is unnecessary. Advantages of this approach are that it employs simple and universal description of plate geometry and yields a complete, smoothed, precise mathematical equation of the plate that is suitable for modern three dimensional production. It is quite general and suitable for both exterior and interior plate surfaces, yielding the ability to control thicknesses along with shape. This method can produce mathematical descriptions with tolerances easily less than 0.001 millimeters suitable for modern computerized numerical control carving and hand finishing.

Adults are skilled at perceiving subjective contours in regions without any local image information (e.g., [Ginsburg, 1975] and [Kanizsa, 1976]). Here we examined the development of this skill and the effect thereon of the support ratio (i.e., the ratio of the physically specified contours to the total contour length). Children (6-, 9-, and…

Contour trees can represent the topology of large volume data sets in a relatively compact, discrete data structure. However, the resulting trees often contain many thousands of nodes; thus, many graph drawing techniques fail to produce satisfactory results. Therefore, several visualization methods...... were proposed recently for the visualization of contour trees. Unfortunately, none of these techniques is able to handle uncertain contour trees although any uncertainty of the volume data inevitably results in partially uncertain contour trees. In this work, we visualize uncertain contour trees...... by combining the contour trees of two morphologically filtered versions of a volume data set, which represent the range of uncertainty. These two contour trees are combined and visualized within a single image such that a range of potential contour trees is represented by the resulting visualization. Thus...

Purpose: Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D beams-eye-view from the conventional simulator. To analyze the outcomes of such treatments for radiation late effects, 3D computational human models are often used in commercial treatment planning systems (TPSs). However, several underlying difficulties such as time-consuming manual delineation procedures of a large number of structures in the model have always limited its applications. Primary objective of this work was to develop a human model library for the epidemiological study by converting 3D-surface model organs to DICOM-RT format (DICOM-RT structure) using an in-house built software. We converted the ICRP reference human models to DICOM-RT models, which can be readily adopted for various dose calculations. Methods: MATLAB based code were utilized to convert the contour drawings extracted in text-format from the 3D graphic-tool, Rhinoceros into DICOM-RT structure format for 50 different organs of each model using a 16GB dual-core processor. The conversion periods were measured for each DICOM-RT models, and the reconstructed structure volumes were validated against the original 3D-surface models in the TPS. Ten reference hybrid whole-body models (8-pediatric and 2-adults) were automatically processed to create DICOM-RT computational human model library. Results: Mean contour conversion period was found to be 580 (N=2) and 394.5 (N=8) seconds for 50 organs in the adult and pediatric models respectively. A good agreement for large organs (NRMSD <1.0%) and small organs (NRMSD <7.7%) was also observed between the original volumes and corresponding DICOM-RT structure volumes of the organs. Conclusion: The ICRP reference human models were converted into DICOM-RT format to support the epidemiological study using a large cohort of conventional radiotherapy patients. Due to its DICOM-compatibility, the library may be implemented to many other different

Purpose: Prior to 3D conformal radiation therapy planning, patient anatomy information was mostly limited to 2D beams-eye-view from the conventional simulator. To analyze the outcomes of such treatments for radiation late effects, 3D computational human models are often used in commercial treatment planning systems (TPSs). However, several underlying difficulties such as time-consuming manual delineation procedures of a large number of structures in the model have always limited its applications. Primary objective of this work was to develop a human model library for the epidemiological study by converting 3D-surface model organs to DICOM-RT format (DICOM-RT structure) using an in-house built software. We converted the ICRP reference human models to DICOM-RT models, which can be readily adopted for various dose calculations. Methods: MATLAB based code were utilized to convert the contour drawings extracted in text-format from the 3D graphic-tool, Rhinoceros into DICOM-RT structure format for 50 different organs of each model using a 16GB dual-core processor. The conversion periods were measured for each DICOM-RT models, and the reconstructed structure volumes were validated against the original 3D-surface models in the TPS. Ten reference hybrid whole-body models (8-pediatric and 2-adults) were automatically processed to create DICOM-RT computational human model library. Results: Mean contour conversion period was found to be 580 (N=2) and 394.5 (N=8) seconds for 50 organs in the adult and pediatric models respectively. A good agreement for large organs (NRMSD <1.0%) and small organs (NRMSD <7.7%) was also observed between the original volumes and corresponding DICOM-RT structure volumes of the organs. Conclusion: The ICRP reference human models were converted into DICOM-RT format to support the epidemiological study using a large cohort of conventional radiotherapy patients. Due to its DICOM-compatibility, the library may be implemented to many other different

There remains a gap in our knowledge base about neural representation of pitch attributes that occur between onset and offset of dynamic, curvilinear pitch contours. The aim is to evaluate how language experience shapes processing of pitch contours as reflected in the amplitude of cortical pitch-specific response components. Responses were elicited from three nonspeech, bidirectional (falling-rising) pitch contours representative of Mandarin Tone 2 varying in location of the turning point with fixed onset and offset. At the frontocentral Fz electrode site, Na–Pb and Pb–Nb amplitude of the Chinese group was larger than the English group for pitch contours exhibiting later location of the turning point relative to the one with the earliest location. Chinese listeners’ amplitude was also greater than that of English in response to those same pitch contours with later turning points. At lateral temporal sites (T7/T8), Na–Pb amplitude was larger in Chinese listeners relative to English over the right temporal site. In addition, Pb–Nb amplitude of the Chinese group showed a rightward asymmetry. The pitch contour with its turning point located about halfway of total duration evoked a rightward asymmetry regardless of group. These findings suggest that neural mechanisms processing pitch in the right auditory cortex reflect experience-dependent modulation of sensitivity to weighted integration of changes in acceleration rates of rising and falling sections and the location of the turning point. PMID:28713201

Full Text Available Acute Myeloid Leukemia (AML is a type of cancer which attacks white blood cells from myeloid. AML has eight subtypes, namely: M0, M1, M2, M3, M4, M5, M6, and M7. AML subtypes M1, M2 and M3 are affected by the same type of cells, myeloblast, making it needs more detailed analysis to distinguish. To overcome these obstacles, this research is applying digital image processing with ActiveContour Without Edge (ACWE and Momentum Backpropagation artificial neural network for AML subtypes M1, M2 and M3 classification based on the type of the cell. Six features required as training parameters from every cell obtained by using feature extraction. The features are: cell area, perimeter, circularity, nucleus ratio, mean and standard deviation. The results show that ACWE can be used for segmenting white blood cells with 83.789% success percentage of 876 total cell objects. The whole AML slides had been identified according to the cell types predicted number through training with momentum backpropagation. Five times testing calibration with the best parameter generated averages value of 84.754% precision, 75.887% sensitivity, 95.090% specificity and 93.569% accuracy.

Full Text Available Visualization of the entire length of the gastrointestinal tract through natural orifices is a challenge for endoscopists. Videoendoscopy is currently the “gold standard” technique for diagnosis of different pathologies of the intestinal tract. Wireless capsule endoscopy (WCE has been developed in the 1990s as an alternative to videoendoscopy to allow direct examination of the gastrointestinal tract without any need for sedation. Nevertheless, the systematic postexamination by the specialist of the 50,000 (for the small bowel to 150,000 images (for the colon of a complete acquisition using WCE remains time-consuming and challenging due to the poor quality of WCE images. In this paper, a semiautomatic segmentation for analysis of WCE images is proposed. Based on activecontour segmentation, the proposed method introduces alpha-divergences, a flexible statistical similarity measure that gives a real flexibility to different types of gastrointestinal pathologies. Results of segmentation using the proposed approach are shown on different types of real-case examinations, from (multipolyp(s segmentation, to radiation enteritis delineation.

This dissertation describes the quantitation of myocardial perfusion defects in planar thallium-201 scintigrams. To be able to quantify the distribution of 201 Tl in the myocardium as imaged by the scintigram, accurate delineation of the target object is a prerequisite. The distribution of the radionuclide within the contour of the left ventricle can be described by application of circumferential profiles. By comparing the computed circumferential profile with those of normal subjects, humans with no evidence of coronary artery disease, segments of the left ventricle with decreased bloodflow can be detected. In practice there is no real standard to compare with, and due to noise and biological variations, it is not always possible to make a definite decision regarding the presence of a defect in the distribution of the radionuclide. The value and limitations of the developed quantification procedure are discussed. Some future developments are suggested. 108 refs.; 57 figs.; 5 tabs

Purpose: To evaluate the clinical application of a robust semiautomatic image segmentation method to determine the brain target volumes in radiation therapy treatment planning. Methods and Materials: A local robust region-based algorithm was used on MRI brain images to study the clinical target volume (CTV) of several patients. First, 3 oncologists delineated CTVs of 10 patients manually, and the process time for each patient was calculated. The averages of the oncologists’ contours were evaluated and considered as reference contours. Then, to determine the CTV through the semiautomatic method, a fourth oncologist who was blind to all manual contours selected 4-8 points around the edema and defined the initial contour. The time to obtain the final contour was calculated again for each patient. Manual and semiautomatic segmentation were compared using 3 different metric criteria: Dice coefficient, Hausdorff distance, and mean absolute distance. A comparison also was performed between volumes obtained from semiautomatic and manual methods. Results: Manual delineation processing time of tumors for each patient was dependent on its size and complexity and had a mean (±SD) of 12.33 ± 2.47 minutes, whereas it was 3.254 ± 1.7507 minutes for the semiautomatic method. Means of Dice coefficient, Hausdorff distance, and mean absolute distance between manual contours were 0.84 ± 0.02, 2.05 ± 0.66 cm, and 0.78 ± 0.15 cm, and they were 0.82 ± 0.03, 1.91 ± 0.65 cm, and 0.7 ± 0.22 cm between manual and semiautomatic contours, respectively. Moreover, the mean volume ratio (=semiautomatic/manual) calculated for all samples was 0.87. Conclusions: Given the deformability of this method, the results showed reasonable accuracy and similarity to the results of manual contouring by the oncologists. This study shows that the localized region-based algorithms can have great ability in determining the CTV and can be appropriate alternatives for manual approaches in brain cancer.

Purpose: To evaluate the clinical application of a robust semiautomatic image segmentation method to determine the brain target volumes in radiation therapy treatment planning. Methods and Materials: A local robust region-based algorithm was used on MRI brain images to study the clinical target volume (CTV) of several patients. First, 3 oncologists delineated CTVs of 10 patients manually, and the process time for each patient was calculated. The averages of the oncologists’ contours were evaluated and considered as reference contours. Then, to determine the CTV through the semiautomatic method, a fourth oncologist who was blind to all manual contours selected 4-8 points around the edema and defined the initial contour. The time to obtain the final contour was calculated again for each patient. Manual and semiautomatic segmentation were compared using 3 different metric criteria: Dice coefficient, Hausdorff distance, and mean absolute distance. A comparison also was performed between volumes obtained from semiautomatic and manual methods. Results: Manual delineation processing time of tumors for each patient was dependent on its size and complexity and had a mean (±SD) of 12.33 ± 2.47 minutes, whereas it was 3.254 ± 1.7507 minutes for the semiautomatic method. Means of Dice coefficient, Hausdorff distance, and mean absolute distance between manual contours were 0.84 ± 0.02, 2.05 ± 0.66 cm, and 0.78 ± 0.15 cm, and they were 0.82 ± 0.03, 1.91 ± 0.65 cm, and 0.7 ± 0.22 cm between manual and semiautomatic contours, respectively. Moreover, the mean volume ratio (=semiautomatic/manual) calculated for all samples was 0.87. Conclusions: Given the deformability of this method, the results showed reasonable accuracy and similarity to the results of manual contouring by the oncologists. This study shows that the localized region-based algorithms can have great ability in determining the CTV and can be appropriate alternatives for manual approaches in brain cancer

The possibility of monitoring changes in aortic elasticity in humans has important applications for clinical trials because it estimates the efficacy of plaque-reducing therapies. The elasticity is usually quantified by compliance measurements. Therefore, the relative temporal change in the vessel cross-sectional area throughout the cardiac cycle has to be determined. In this work we determined and compared the compliance between three magnetic resonance (MR) methods (FLASH, TrueFISP and pulse-wave). Since manual outlining of the aortic wall area is a very time-consuming process and depends on an operator's variability, an algorithm for the automatic segmentation of the artery wall from MR images through the entire heart cycle is presented. The reliable detection of the artery cross-sectional area over the whole heart cycle was possible with a relative error of about 1%. Optimizing the temporal resolution to 60 ms we obtained a relative error in compliance of about 7% from TrueFISP (1.0 x 1.0 x 10 mm 3 , signal-to-noise ratio (SNR) > 12) and FLASH (0.7 x 0.7 x 10 mm 3 , SNR > 12) measurements in volunteers. Pulse-wave measurements yielded an error of more than 9%. In a study of ten volunteers, a compliance between C = 3 x 10 -5 Pa -1 and C = 8 x 10 -5 Pa -1 was determined, depending on age. The results of the TrueFISP and the pulse-wave measurements agreed very well with one another (confidence interval of 1 x 10 -5 Pa -1 ) while the results of the FLASH method more clearly deviated from the TrueFISP and pulse-wave (confidence interval of more than 2 x 10 -5 Pa -1 )

of the processes requires the extraction of characteristic parameters of the welding groove close to the molten pool, i.e. in an environment dominated by the very intense light emission from the welding arc. The typical industrial solution today is a laser-scanner containing a camera as well as a laser source......In the recent decades much research has been performed in order to allow better control of arc welding processes, but the success has been limited, and the vast majority of the industrial structural welding work is therefore still being made manually. Closed-loop and nearly-closed-loop control...... illuminating the groove by a light curtain and thus allowing details of the groove geometry to be extracted by triangulation. This solution is relatively expensive and must act several centimetres ahead of the molten pool. In addition laser-scanners often show problems when dealing with shiny surfaces...

An approach is outlined to the recognition of contour images using computer technology based on coherent optics principles. A mathematical description of the recognition process algorithm and the results of numerical modelling are presented. The developed approach to the recognition of contour images using optics of spiral beams is described and justified.

Psychophysical and neurophysiological evidence about the human visual system shows the existence of a mechanism, called surround suppression, which inhibits the response of an edge in the presence of other similar edges in the surroundings. A simple computational model of this phenomenon has been

Two basic techniques for extracting interferogram contours have been discussed. The first is a global contour extracton technique based on the fast Fourier transform. The second extracts individual contours with a thinning algorithm using logical neighborhood transformations

Theoretical analyses and experimental results on holographic moire contouring on diffusely reflecting objects are presented. The sensitivity and limitations of the method are discussed. Particular emphasis is put on computer-assisted data retrieval, processing, and recording.

Many of the topological features of the isosurfaces of a scalar volume field can be compactly represented by its contour tree. Unfortunately, the contour trees of most real-world volume data sets are too complex to be visualized by dot-and-line diagrams. Therefore, we propose a new visualization...... that is suitable for large contour trees and efficiently conveys the topological structure of the most important isosurface components. This visualization is integrated into a histogram of the volume data; thus, it offers strictly more information than a traditional histogram. We present algorithms...... to automatically compute the graph layout and to calculate appropriate approximations of the contour tree and the surface area of the relevant isosurface components. The benefits of this new visualization are demonstrated with the help of several publicly available volume data sets....

Image interpolation is the problem of increasing the resolution of an image. Linear methods must compromise between artifacts like jagged edges, blurring, and overshoot (halo) artifacts. More recent works consider nonlinear methods to improve interpolation of edges and textures. In this paper we apply contour stencils for estimating the image contours based on total variation along curves and then use this estimation to construct a fast edge-adaptive interpolation.

The dosimetric calculation in patients that receive radiotherapy treatment it requires the one knowledge of the geometry of some anatomical portions, which differs from a patient to another. Making reference to the specific case of mammary neoplasia, one of the measurements that is carried out on the patient is the acquisition of the contour of the breast, which is determined from a point marked on the breastbone until another point marked on the lateral of the thorax, below the armpit, with the patient located in the irradiation position. This measurement is carried out with the help of a mechanical contour meter that is a device conformed by a series of wires with a polymeric coating, which support on the breast of the patient and it reproduces its form. Then it is transported in the more careful possible form on a paper and the contour is traced with a tracer one. The geometric error associated to this procedure is of ±1 cm, which is sensitive of being reduced. The present work finds its motivation in the patient's radiological protection radiotherapy. The maximum error in dose allowed in radiotherapeutic treatments is 5%. It would be increase the precision and with it to optimize the treatment received by the patient, reducing the error in the acquisition process of the mammary contour. With this objective, a digital device is designed whose operation is based in the application of a spatial transformation on a picture of the mammary contour, which corrects the geometric distortion introduced in the process of the photographic acquisition. An algorithm that allows to obtain a front image (without distortion) of the plane of the contour was developed. A software tool especially developed carries out the processing of the digital images. The maximum geometric error detected in the validation process is 2 mm located on a small portion of the contour. (Author)

Fully or semi-automatic contouring tools are increasingly being used in the tumor contouring task for radiotherapy. While the fully automatic contouring tools have not reached sufficient efficiency, the semi-automatic contouring tools balance more effectively between the human interaction and

We examined how crowding (the breakdown of object recognition in the periphery caused by interference from "clutter") depends on the global arrangement of target and distracting flanker elements. Specifically we probed orientation discrimination using a near-vertical target Gabor flanked by two vertical distractor Gabors (one above and one below the target). By applying variable (opposite-sign) horizontal offsets to the positions of the two flankers we arranged the elements so that on some trials they formed contours with the target and on others they did not. While the presence of flankers generally elevated orientation discrimination thresholds for the target we observe maximal crowding not when flanker and targets were co-aligned but when a small spatial offset was applied to flanker location, so that contours formed between flanker and targets only when the target orientation was cued. We also report that observers' orientation judgments are biased, with target orientation appearing either attracted or repulsed by the global/contour orientation. A second experiment reveals that the sign of this effect is dependent both on observer and on eccentricity. In general, the magnitude of repulsion is reduced with eccentricity but whether this becomes attraction (of element orientation to contour orientation) is dependent on observer. We note however that across observers and eccentricities, the magnitude of repulsion correlates positively with the amount of release from crowding observed with co-aligned targets and flankers, supporting the notion of fluctuating bias as the basis for elevated crowding within contours.

Motivated by a variational model concerning the depth of the objects in a picture and the problem of hidden and illusory contours, this book investigates one of the central problems of computer vision: the topological and algorithmic reconstruction of a smooth three dimensional scene starting from the visible part of an apparent contour. The authors focus their attention on the manipulation of apparent contours using a finite set of elementary moves, which correspond to diffeomorphic deformations of three dimensional scenes. A large part of the book is devoted to the algorithmic part, with implementations, experiments, and computed examples. The book is intended also as a user's guide to the software code appcontour, written for the manipulation of apparent contours and their invariants. This book is addressed to theoretical and applied scientists working in the field of mathematical models of image segmentation.

Inter-observer variability is the lack of agreement among clinicians in contouring a given organ or tumour in a medical image. The variability in medical image contouring is a source of uncertainty in radiation treatment planning. Consensus contour of a given case, which was proposed to reduce the variability, is generated by combining the manually generated contours of several clinicians. However, having access to several clinicians (e.g., radiation oncologists) to generate a consensus contour for one patient is costly. This paper presents an algorithm that automatically generates a consensus contour for a given case using the atlases of different clinicians. The algorithm was applied to prostate MR images of 15 patients manually contoured by 5 clinicians. The automatic consensus contours were compared to manual consensus contours where a median Dice similarity coefficient (DSC) of 88% was achieved.

Full Text Available An algorithm for the estimation of chin and cheek contours in video sequences is proposed. This algorithm exploits a priori knowledge about shape and position of chin and cheek contours in images. Exploiting knowledge about the shape, a parametric 2D model representing chin and cheek contours is introduced. Exploiting knowledge about the position, a MAP estimator is developed taking into account the observed luminance gradient as well as a priori probabilities of chin and cheek contours positions. The proposed algorithm was tested with head and shoulder video sequences (image resolution CIF. In nearly 70% of all investigated video frames, a subjectively error free estimation could be achieved. The 2D estimate error is measured as on average between 2.4 and .

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model ...

The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future

The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.

The purpose of this work is to develop an effective technique to automatically propagate contours from planning CT to cone beam CT (CBCT) to facilitate CBCT-guided prostate adaptive radiation therapy. Different from other disease sites, such as the lungs, the contour mapping here is complicated by two factors: (i) the physical one-to-one correspondence may not exist due to the insertion or removal of some image contents within the region of interest (ROI); and (ii) reduced contrast to noise ratio of the CBCT images due to increased scatter. To overcome these issues, we investigate a strategy of excluding the regions with variable contents by a careful design of a narrow shell signifying the contour of an ROI. For rectum, for example, a narrow shell with the delineated contours as its interior surface was constructed to avoid the adverse influence of the day-to-day content change inside the rectum on the contour mapping. The corresponding contours in the CBCT were found by warping the narrow shell through the use of BSpline deformable model. Both digital phantom experiments and clinical case testing were carried out to validate the proposed ROI mapping method. It was found that the approach was able to reliably warp the constructed narrow band with an accuracy better than 1.3 mm. For all five clinical cases enrolled in this study, the method yielded satisfactory results even when there were significant rectal content changes between the planning CT and CBCT scans. The overlapped area of the auto-mapped contours over 90% to the manually drawn contours is readily achievable. The proposed approach permits us to take advantage of the regional calculation algorithm yet avoiding the nuisance of rectum/bladder filling and provide a useful tool for adaptive radiotherapy of prostate in the future.

To develop automatic and efficient liver contouring software for planning 3D-CT and four-dimensional computed tomography (4D-CT) for application in clinical radiation therapy treatment planning systems.The algorithm comprises three steps for overcoming the challenge of similar intensities between the liver region and its surrounding tissues. First, the total variation model with the L1 norm (TV-L1), which has the characteristic of multi-scale decomposition and an edge-preserving property, is used for removing the surrounding muscles and tissues. Second, an improved level set model that contains both global and local energy functions is utilized to extract liver contour information sequentially. In the global energy function, the local correlation coefficient (LCC) is constructed based on the gray level co-occurrence matrix both of the initial liver region and the background region. The LCC can calculate the correlation of a pixel with the foreground and background regions, respectively. The LCC is combined with intensity distribution models to classify pixels during the evolutionary process of the level set based method. The obtained liver contour is used as the candidate liver region for the following step. In the third step, voxel-based texture characterization is employed for refining the liver region and obtaining the final liver contours.The proposed method was validated based on the planning CT images of a group of 25 patients undergoing radiation therapy treatment planning. These included ten lung cancer patients with normal appearing livers and ten patients with hepatocellular carcinoma or liver metastases. The method was also tested on abdominal 4D-CT images of a group of five patients with hepatocellular carcinoma or liver metastases. The false positive volume percentage, the false negative volume percentage, and the dice similarity coefficient between liver contours obtained by a developed algorithm and a current standard delineated by the expert group

Full Text Available Abstract Background Electromagnetic stimulation of the nervous system has the advantage of reduced discomfort in activating nerves. For brain structures stimulation, it has become a clinically accepted modality. Coil designs usually consider factors such as optimization of induced power, focussing, field shape etc. In this study we are attempting to find the effect of the coil contour shape on the electrical field distribution for magnetic stimulation. Method and results We use the maximum of the induced electric field stimulation in the region of interest as the optimization criterion. This choice required the application of the calculus of variation, with the contour perimeter taken as a pre-set condition. Four types of coils are studied and compared: circular, square, triangular and an 'optimally' shaped contour. The latter yields higher values of the induced electrical field in depths up to about 30 mm, but for depths around 100 mm, the circular shape has a slight advantage. The validity of the model results was checked by experimental measurements in a tank with saline solution, where differences of about 12% were found. In view the accuracy limitations of the computational and measurement methods used, such differences are considered acceptable. Conclusion We applied an optimization approach, using the calculus of variation, which allows to obtain a coil contour shape corresponding to a selected criterion. In this case, the optimal contour showed higher intensities for a longer line along the depth-axis. The method allows modifying the induced field structure and focussing the field to a selected zone or line.

Template matching is a significant approach in machine vision due to its effectiveness and robustness. However, most of the template matching methods are so time consuming that they can't be used to many real time applications. The closed contour matching method is a popular kind of template matching methods. This paper presents a new closed contour template matching method which is suitable for two dimensional objects. Coarse-to-fine searching strategy is used to improve the matching efficiency and a partial computation elimination scheme is proposed to further speed up the searching process. The method consists of offline model construction and online matching. In the process of model construction, triples and distance image are obtained from the template image. A certain number of triples which are composed by three points are created from the contour information that is extracted from the template image. The rule to select the three points is that the template contour is divided equally into three parts by these points. The distance image is obtained here by distance transform. Each point on the distance image represents the nearest distance between current point and the points on the template contour. During the process of matching, triples of the searching image are created with the same rule as the triples of the model. Through the similarity that is invariant to rotation, translation and scaling between triangles, the triples corresponding to the triples of the model are found. Then we can obtain the initial RST (rotation, translation and scaling) parameters mapping the searching contour to the template contour. In order to speed up the searching process, the points on the searching contour are sampled to reduce the number of the triples. To verify the RST parameters, the searching contour is projected into the distance image, and the mean distance can be computed rapidly by simple operations of addition and multiplication. In the fine searching process

The ability to integrate visual features into a global coherent percept that can be further categorized and manipulated are fundamental abilities of the neural system. While the processing of visual information involves activation of early visual cortices, the recruitment of parietal and frontal cortices has been shown to be crucial for perceptual processes. Yet is it not clear how both cortical and long-range oscillatory activity leads to the integration of visual features into a coherent percept. Here, we will investigate perceptual grouping through the analysis of a contour categorization task, where the local elements that form contour must be linked into a coherent structure, which is then further processed and manipulated to perform the categorization task. The contour formation in our visual stimulus is a dynamic process where, for the first time, visual perception of contours is disentangled from the onset of visual stimulation or from motor preparation, cognitive processes that until now have been behaviorally attached to perceptual processes. Our main finding is that, while local and long-range synchronization at several frequencies seem to be an ongoing phenomena, categorization of a contour could only be predicted through local oscillatory activity within parietal/frontal sources, which in turn, would synchronize at gamma (>30 Hz) frequency. Simultaneously, fronto-parietal beta (13-30 Hz) phase locking forms a network spanning across neural sources that are not category specific. Both long range networks, i.e., the gamma network that is category specific, and the beta network that is not category specific, are functionally distinct but spatially overlapping. Altogether, we show that a critical mechanism underlying contour categorization involves oscillatory activity within parietal/frontal cortices, as well as its synchronization across distal cortical sites.

Contours are important data to delineate the landform on a map. A contour tree provides an object-oriented description of landforms and can be used to enrich the topological information. The traditional contour tree is used to store topological relationships between contours in a hierarchical structure and allows for the identification of eminences and depressions as sets of nested contours. This research proposes an improved contour tree so-called spatial contour tree that contains not only the topological but also the geometric information. It can be regarded as a terrain skeleton in 3-dimention, and it is established based on the spatial nodes of contours which have the latitude, longitude and elevation information. The spatial contour tree is built by connecting spatial nodes from low to high elevation for a positive landform, and from high to low elevation for a negative landform to form a hierarchical structure. The connection between two spatial nodes can provide the real distance and direction as a Euclidean vector in 3-dimention. In this paper, the construction method is tested in the experiment, and the results are discussed. The proposed hierarchical structure is in 3-demintion and can show the skeleton inside a terrain. The structure, where all nodes have geo-information, can be used to distinguish different landforms and applied for contour generalization with consideration of geographic characteristics.

Full Text Available Presenting luminance contours surrounding the adapted areas in test phase enhances color afterimages in both duration and color appearance. The presence of surrounding contour is crucial to some color phenomenon such as van Lier's afterimage, but the contour-effect itself has not been seriously examined. In this paper, we compared the contour-effect to color afterimages and to actually colored patches to examine the nature of color information subserving color-aftereffect. In the experiment, observers were adapted for 1 sec to a small colored square (red, green, yellow, or blue presented on a gray background. Then, a test field either with or without surrounding contour was presented. Observers matched the color of a test-patch located near the afterimage to the color of afterimage. It was found that the saturation of negative afterimage was almost doubled by the presence of surrounding contours. There was no effect of luminance contrast or polarity of contours. In contrast, no enhancement of saturation by surrounding contours was observed for actually colored patches even though the colors of patches were equalized to that of afterimage without contours. This dissociation in the contour-effect demonstrates the crucial difference between the color information for aftereffects and for ordinary bottom-up color perception.

Full Text Available Chromatic induction is observed whenever the perceived colour of a target surface shifts towards the hue of a neighbouring surface. Some vivid manifestations may be seen in a white background where thin coloured lines have been drawn (assimilation or when lines of different colours are collinear (neon effect or adjacent (watercolour to each other. This study examines a particular colour induction that manifests in concomitance with an opposite effect of colour saturation (or anti-spread. The two phenomena can be observed when a repetitive pattern is drawn in which outline thin contours intercept wider contours or surfaces, colour spreading appear to fill the surface occupied by surfaces or thick lines whereas the background traversed by thin lines is seen as brighter or filled of a saturated white. These phenomena were first observed by Bozzi (1975 and Kanizsa (1979 in figural conditions that did not allow them to document their conjunction. Here we illustrate various manifestations of this twofold phenomenon and compare its effects with the known effects of brightness and colour induction. Some conjectures on the nature of these effects are discussed.

Massive weight loss following bariatric surgery leads to excess skin with functional and aesthetic impairments. Surplus skin can then contribute to problems with additional weight loss or gain. The aims of the current study were to evaluate the frequency of massive soft tissue development in gastric bypass patients, to determine whether males and females experience similar post-bypass body changes, and to learn about the expectations and impairments related to body contouring surgery. A questionnaire addressing information on the satisfaction of body image, quality of life, and expectation of body contouring surgery following massive weight loss was mailed to 425 patients who had undergone gastric bypass surgery between 2003 and 2009. Of these 425 individuals, 252 (59%) patients completed the survey. Ninety percent of women and 88% of men surveyed rated their appearance following massive weight loss as satisfactory, good, or very good. However, 96% of all patients developed surplus skin, which caused intertriginous dermatitis and itching. In addition, patients reported problems with physical activity (playing sports) and finding clothing that fit appropriately. Moreover, 75% of female and 68% of male patients reported desiring body contouring surgery. The most important expectation of body contouring surgery was improved appearance, followed by improved self-confidence and quality of life. Surplus skin resulting from gastric bypass surgery is a common issue that causes functional and aesthetic impairments in patients. Consequently, this increases the desire for body contouring surgery with high expectations for the aesthetic outcome as well as improved life satisfaction.

Purpose: To describe a method for unified description, statistical modeling, and comparison of voice range profile (VRP) contours, even from diverse sources. Method: A morphologic modeling technique, which is based on Fourier descriptors (FDs), is applied to the VRP contour. The technique, which essentially involves resampling of the curve of the…

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model.

Full Text Available The edge detection techniques have to compromise between sensitivity and noise. In order for the main contours to be uninterrupted, the level of sensitivity has to be raised, which however has the negative effect of producing a multitude of insignificant contours (noise. This article proposes a method of removing this noise, which acts directly on the binary representation of the image contours.

Full Text Available The need for a paradigm change in economic thought has been well established, but the contours and fundamental characteristics of a new paradigm in economic theory are yet to be worked out. This article views this transition as an inevitable expression of the maturation of the social sciences into an integrated trans-disciplinary science of society founded on common underlying principles, premises and processes. It calls for evolution of human-centered, value-based economic theory whose objective is to maximize human economic security, welfare and well-being rather than economic growth. It emphasizes the determinative role of fundamental creative social processes expressing in all fields of human endeavor. It argues for extending the boundaries of economics to encompass the entire gamut of political, legal, social, psychological, intellectual, organizational and ecological factors that directly and indirectly contribute to economic security, welfare and well-being. The article concludes with a list of anticipated practical implications.

Purpose/Objective(s): Adaptive techniques allow for correction of spatial changes during the time course of the fractionated radiotherapy. Spatial changes include tumor shrinkage and weight loss, causing tissue deformation and residual positional errors even after translational and rotational image...... the planning CT onto the rescans and correcting to reflect actual anatomical changes. For deformable registration, a free-form, multi-level, B-spline deformation model with Riemannian elasticity, penalizing non-rigid local deformations, and volumetric changes, was used. Regularization parameters was defined...... on the original delineation and tissue deformation in the time course between scans form a better starting point than rigid propagation. There was no significant difference of locally and globally defined regularization. The method used in the present study suggests that deformed contours need to be reviewed...

Active shape models (ASM) are widely employed for recognizing anatomic structures and for delineating them in medical images. In this paper, a novel strategy called oriented active shape models (OASM) is presented in an attempt to overcome the following five limitations of ASM: 1) lower delineation accuracy, 2) the requirement of a large number of landmarks, 3) sensitivity to search range, 4) sensitivity to initialization, and 5) inability to fully exploit the specific information present in the given image to be segmented. OASM effectively combines the rich statistical shape information embodied in ASM with the boundary orientedness property and the globally optimal delineation capability of the live wire methodology of boundary segmentation. The latter characteristics allow live wire to effectively separate an object boundary from other nonobject boundaries with similar properties especially when they come very close in the image domain. The approach leads to a two-level dynamic programming method, wherein the first level corresponds to boundary recognition and the second level corresponds to boundary delineation, and to an effective automatic initialization method. The method outputs a globally optimal boundary that agrees with the shape model if the recognition step is successful in bringing the model close to the boundary in the image. Extensive evaluation experiments have been conducted by utilizing 40 image (magnetic resonance and computed tomography) data sets in each of five different application areas for segmenting breast, liver, bones of the foot, and cervical vertebrae of the spine. Comparisons are made between OASM and ASM based on precision, accuracy, and efficiency of segmentation. Accuracy is assessed using both region-based false positive and false negative measures and boundary-based distance measures. The results indicate the following: 1) The accuracy of segmentation via OASM is considerably better than that of ASM; 2) The number of landmarks

The contour tree compactly describes scalar field topology. From the viewpoint of graph drawing, it is a tree with attributes at vertices and optionally on edges. Standard tree drawing algorithms emphasize structural properties of the tree and neglect the attributes. Applying known techniques to convey this information proves hard and sometimes even impossible. We present several adaptions of popular graph drawing approaches to the problem of contour tree drawing and evaluate them. We identify five esthetic criteria for drawing contour trees and present a novel algorithm for drawing contour trees in the plane that satisfies four of these criteria. Our implementation is fast and effective for contour tree sizes usually used in interactive systems (around 100 branches) and also produces readable pictures for larger trees, as is shown for an 800 branch example.

With tonometers currently in use intraocular pressure is indirectly determined by measuring a physical quantity related to a specified deformation of the cornea. We present a new principle of direct, continuous, and transcorneal intraocular pressure measurement, describe its theoretical foundation, and evaluate its application on the basis of an in vitro model. On a living human eye an optimized pressure-sensitive contact surface was determined by performing pressure measurements with differently shaped tonometer heads. Based on these results and on the theoretical model, a Dynamic Contour Tonometer was constructed and validated on eye bank bulbi against a manometric reference pressure. A concave contact surface with a radius of curvature of 10.5 mm creates a distribution of forces between the central contour matching area of the tip and the cornea that equals the forces generated by the internal pressure of the eye. A sensor integrated into the surface having the same contour measures the intraocular pressure closely to the manometric reference pressure in human cadaver eyes. The accuracy of the tonometer appears to be unaffected by variations in corneal properties. Dynamic Contour Tonometry eliminates most of the systematic errors arising from individual changes of corneal properties that adversely influence all types of applanation tonometers. The advantage of measuring the true pressure in combination with the capability of registering dynamic pressure fluctuations discloses new tonometric opportunities to diagnose and classify different types of glaucoma.

Full Text Available Accurate target delineation of CT image is a critical step in radiotherapy treatment planning. This paper describes a novel strategy for automatic contour propagation, based on deformable registration, for CT images of lung cancer. The proposed strategy starts with a manual-delineated contour in one slice of a 3D CT image. By means of feature-based deformable registration, the initial contour in other slices of the image can be propagated automatically, and then refined by activecontour approach. Three algorithms are employed in the strategy: the Speeded-Up Robust Features (SURF, Thin-Plate Spline (TPS, and an adapted activecontour (Snake, used to refine and modify the initial contours. Five pulmonary cancer cases with about 400 slices and 1000 contours have been used to verify the proposed strategy. Experiments demonstrate that the proposed strategy can improve the segmentation performance in the pulmonary CT images. Jaccard similarity (JS mean is about 0.88 and the maximum of Hausdorff distance (HD is about 90%. In addition, delineation time has been considerably reduced. The proposed feature-based deformable registration method in the automatic contour propagation improves the delineation efficiency significantly.

An important task of vision is the segregation of figure and ground in situations of spatial occlusion. Psychophysical evidence suggests that the depth order at contours is defined early in visual processing. We have analysed this process in the visual cortex of the alert monkey. The animals were trained on a visual fixation task which reinforced foveal viewing. During periods of active visual fixation, we recorded the responses of single neurons in striate and prestriate cortex (areas V1, V2, and V3/V3A). The stimuli mimicked situations of spatial occlusion, usually a uniform light (or dark) rectangle overlaying a grating texture of opposite contrast. The direction of figure and ground at the borders of these rectangles was defined by the direction of the terminating grating lines (occlusion cues). Neuronal responses were analysed with respect to figure-ground direction and contrast polarity at such contours. Striate neurons often failed to respond to such stimuli, or were selective for contrast polarity; others were non-selective. Some neurons preferred a certain combination of figure-ground direction and contrast polarity. These neurons were rare both in striate and prestriate cortex. The majority of neurons signalled figure-ground direction independent of contrast polarity. These neurons were only found in prestriate cortex. We explain these responses in terms of a model which also explains neuronal signals of illusory contours. These results suggest that occlusion cues are used at an early level of processing to segregate figure and ground at contours.

Full Text Available We consider the image interpolation problem where given an image vm,n with uniformly-sampled pixels vm,n and point spread function h, the goal is to find function u(x,y satisfying vm,n = (h*u(m,n for all m,n in Z. This article improves upon the IPOL article Image Interpolation with Contour Stencils. In the previous work, contour stencils are used to estimate the image contours locally as short line segments. This article begins with a continuous formulation of total variation integrated over a collection of curves and defines contour stencils as a consistent discretization. This discretization is more reliable than the previous approach and can effectively distinguish contours that are locally shaped like lines, curves, corners, and circles. These improved contour stencils sense more of the geometry in the image. Interpolation is performed using an extension of the method described in the previous article. Using the improved contour stencils, there is an increase in image quality while maintaining similar computational efficiency.

We investigated contour processing and figure-ground detection within human retinotopic areas using event-related functional magnetic resonance imaging (fMRI) in 6 healthy and naïve subjects. A figure (6 degrees side length) was created by a 2nd-order texture contour. An independent and demanding foveal letter-discrimination task prevented subjects from noticing this more peripheral contour stimulus. The contour subdivided our stimulus into a figure and a ground. Using localizers and retinotopic mapping stimuli we were able to subdivide each early visual area into 3 eccentricity regions corresponding to 1) the central figure, 2) the area along the contour, and 3) the background. In these subregions we investigated the hemodynamic responses to our stimuli and compared responses with or without the contour defining the figure. No contour-related blood oxygenation level-dependent modulation in early visual areas V1, V3, VP, and MT+ was found. Significant signal modulation in the contour subregions of V2v, V2d, V3a, and LO occurred. This activation pattern was different from comparable studies, which might be attributable to the letter-discrimination task reducing confounding attentional modulation. In V3a, but not in any other retinotopic area, signal modulation corresponding to the central figure could be detected. Such contextual modulation will be discussed in light of the recurrent processing hypothesis and the role of visual awareness.

The paper presents a method to identify the plasma magnetic contour in fusion machines, when eddy currents are present in the conducting structures surrounding the plasma. The approach presented is based on the integration of an electromagnetic model of the plasma with a lumped parameters model of the conducting structures around the plasma. This approach has been validated against experimental data from RFX, a reversed field pinch machine. (author)

The assessment of the psoas border contour in the X-ray photo of the abdomen is important for differential diagnostic considerations. For the separation of fallacious psoas configurations which are similar to the well defined pathological form changes, a regular supine position of the patient was chosen, and the psoas examined without and with muscle tension. The whole visible psoas muscle system did not show any unilateral bulging of the border silhouette during muscle action. Isolated tension of the left psoas muscle induced a distinct deviation of both border contours to the left side, too. There was a clear tendency of a more distinct psoas border contour and of augmented opacity of the muscle over its whole length under muscle tension. Changes similar to the bulging border contour of a psoas abscess were not produced by muscular action. (orig.) [de

Full Text Available A novel filling-in model is proposed in order to account for challenging brightness illusions where inducing background elements are spatially separated from gray target such as dungeon, cube and grating illusion, bull's eye and ring patterns. The model implements simple idea that neural response to low-contrast contour is enhanced (facilitated by the presence of collinear or parallel high-contrast contour in the wider neighborhood. Contour facilitation is achieved via dendritic inhibition which enables computation of maximum function among inputs to the node. Recurrent application of maximum function leads to the propagation of neural signal along collinear or parallel contour segments. When strong global contour signal is accompanied with weak local contour signal at the same location, conditions are met to produce brightness assimilation within filling-in network. Computer simulations showed that the model correctly predicts brightness appearance in all of the above mentioned illusions as well as in White's effect, Benary's cross, Todorović's illusion, checkerboard contrast, contrast-contrast illusion and various variations on the White's effect. The proposed model offer new insights on how geometric factors (contour colinearity or parallelism jointly with contrast magnitude contribute to the brightness perception.

This report is a part of the reporting of the work done in the project 'Active Control of Wind Turbines'. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to designcontrollers. This report describes the model...... validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending,a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models...

architecture and the UML concepts. In this paper, we further this work by grounding Activity-based DEVS modeling and developing a fully-fledged modeling engine to demonstrate applicability. We also detail the relevant aspects of the created metamodel in terms of modeling and simulation. A significant number......Use of model-driven approaches has been increasing to significantly benefit the process of building complex systems. Recently, an approach for specifying model behavior using UML activities has been devised to support the creation of DEVS models in a disciplined manner based on the model driven...... of the artifacts of the UML 2.5 activities and actions, from the vantage point of DEVS behavioral modeling, is covered in details. Their semantics are discussed to the extent of time-accurate requirements for simulation. We characterize them in correspondence with the specification of the atomic model behavior. We...

This paper provides a brief introduction to antimatter and how it, along with other modern physics topics, is utilized in positron emission tomography (PET) scans. It further describes a hands-on activity for students to help them gain an understanding of how PET scans assist in detecting cancer. Modern physics topics provide an exciting way to introduce students to current applications of physics.

The multivariate image analysis descriptors used in quantitative structure-activity relationships are direct representations of chemical structures as they are simply numerical decodifications of pixels forming the 2D chemical images. These MDs have found great utility in the modeling of diverse properties of organic molecules. Given the multicollinearity and high dimensionality of the data matrices generated with the MIA-QSAR approach, modeling techniques that involve the projection of the data space onto orthogonal components e.g. Partial Least Squares (PLS) have been generally used. However, the chemical interpretation of the PLS-based MIA-QSAR models, in terms of the structural moieties affecting the modeled bioactivity has not been straightforward. This work describes the 2D-contour maps based on the PLS regression coefficients, as a means of assessing the relevance of single MIA predictors to the response variable, and thus allowing for the structural, electronic and physicochemical interpretation of the MIA-QSAR models. A sample study to demonstrate the utility of the 2D-contour maps to design novel drug-like molecules is performed using a dataset of some anti-HIV-1 2-amino-6-arylsulfonylbenzonitriles and derivatives, and the inferences obtained are consistent with other reports in the literature. In addition, the different schemes for encoding atomic properties in molecules are discussed and evaluated.

Researchers from various disciplines have long been interested in analyzing and describing human mobility patterns. Activity space (AS), defined as an area encapsulating daily human mobility and activities, has been at the center of this interest. However, given the applied nature of research in this field and the complexity that advanced geographical modeling can pose to its users, the proposed models remain simplistic and inaccurate in many cases. Individualized Activity Space Modeler (IASM) is a geographic information system (GIS) toolbox, written in Python programming language using ESRI's Arcpy module, comprising four tools aiming to facilitate the use of advanced activity space models in empirical research. IASM provides individual-based and context-sensitive tools to estimate home range distances, delineate activity spaces, and model place exposures using individualized geographical data. In this paper, we describe the design and functionality of IASM, and provide an example of how it performs on a spatial dataset collected through an online map-based survey.

The possibility of applying the mathematical formalism of spiral light beams to the problems of contour image recognition is theoretically studied. The advantages and disadvantages of the proposed approach are evaluated; the results of numerical modelling are presented.

There were four types of stomach contour included eutonic, hypotonic, steerhorn, and cascade. The aim of this study is to clarify relationship between incidence of stomach cancer and contour variation of the stomach. Double- contrast upper gastrointestinal study was performed in 1,546 patients, who had dyspepsia or other gastrointestinal tract symptoms. The radiographs were classified into the four types including eutonic, hypotonic, steerhorn, and cascade according to stomach contour in relation to body build. We also reviewed pathologic reports on endoscopic biopsy or surgical specimen. We studied the presence of relationship between incidence of stomach cancer and variation of stomach contour. We also examined the incidence of gastritis and gastric ulcer to the stomach contour variation. Of total 1,546 patients, eutonic stomach were 438(28.3%), hypotonic 911(58.9%), steerhorn 102(6.5%) and cascade 95(6.2%). Stomach cancer was found in 139(31.7%) of 438 eutonic stomachs, in 135(14.8%) of 911 hypotonic, in 42(41.2%) of 102 steerhorn, and in 24(36.9%) of 95 cascade (P=0.001). In hypotonic stomach, the incidence of stomach cancer was lower compared to the other three types significantly (p<0.05). Gastritis or gastric ulcer was found in 146(33.3%) of eutonic stomach, in 293(32.1%) of hypotonic, in 36(35.2%) of steerhorn, and in 26(27.3%) of cascade (p=0.640). In conclusion, gastric contour variation seems to be a factor affecting development of stomach cancer. The patients with hypotonic stomach may have lower incidence of stomach cancer than that of the other types. There was no relationship between the contour and gastric ulcer

There were four types of stomach contour included eutonic, hypotonic, steerhorn, and cascade. The aim of this study is to clarify relationship between incidence of stomach cancer and contour variation of the stomach. Double- contrast upper gastrointestinal study was performed in 1,546 patients, who had dyspepsia or other gastrointestinal tract symptoms. The radiographs were classified into the four types including eutonic, hypotonic, steerhorn, and cascade according to stomach contour in relation to body build. We also reviewed pathologic reports on endoscopic biopsy or surgical specimen. We studied the presence of relationship between incidence of stomach cancer and variation of stomach contour. We also examined the incidence of gastritis and gastric ulcer to the stomach contour variation. Of total 1,546 patients, eutonic stomach were 438(28.3%), hypotonic 911(58.9%), steerhorn 102(6.5%) and cascade 95(6.2%). Stomach cancer was found in 139(31.7%) of 438 eutonic stomachs, in 135(14.8%) of 911 hypotonic, in 42(41.2%) of 102 steerhorn, and in 24(36.9%) of 95 cascade (P=0.001). In hypotonic stomach, the incidence of stomach cancer was lower compared to the other three types significantly (p<0.05). Gastritis or gastric ulcer was found in 146(33.3%) of eutonic stomach, in 293(32.1%) of hypotonic, in 36(35.2%) of steerhorn, and in 26(27.3%) of cascade (p=0.640). In conclusion, gastric contour variation seems to be a factor affecting development of stomach cancer. The patients with hypotonic stomach may have lower incidence of stomach cancer than that of the other types. There was no relationship between the contour and gastric ulcer.

Research and development activities would involve the scaled modellingactivities in order to investigate theory, facts, thesis or concepts. In commercialisation activities, scaling-up proses is necessary for the development of pilot plants or prototypes. The issue with scaled modelling is the similarity between the small scaled model and the full scaled prototype in all aspects of the system such as physical appearance, dimension and the system behaviour. Similarly, for scaling-up process, physical parameters and behaviour of a smaller model need to be developed into a bigger prototype with similar system. Either way, the modelling process must be able to produce a reliable representation of the system or process so that the objectives or functions of the system can be achieved. This paper discusses a modelling method which may be able to produce similar representation of any system or process either in scaled-model testing or scaling-up processes. (author)

Present image processing algorithms are unable to extract a neat and closed contour of an object of interest from a natural image. Advanced contour detection algorithms extract the contour of an object of interest from a natural scene with a side effect of depletion of the contour. Hence in order to

Purpose: To assess whether an education program on CT and MRI prostate anatomy would reduce inter- and intraobserver prostate contouring variation among experienced radiation oncologists. Methods and Materials: Three patient CT and MRI datasets were selected. Five radiation oncologists contoured the prostate for each patient on CT first, then MRI, and again between 2 and 4 weeks later. Three education sessions were then conducted. The same contouring process was then repeated with the same datasets and oncologists. The observer variation was assessed according to changes in the ratio of the encompassing volume to intersecting volume (volume ratio [VR]), across sets of target volumes. Results: For interobserver variation, there was a 15% reduction in mean VR with CT, from 2.74 to 2.33, and a 40% reduction in mean VR with MRI, from 2.38 to 1.41 after education. A similar trend was found for intraobserver variation, with a mean VR reduction for CT and MRI of 9% (from 1.51 to 1.38) and 16% (from 1.37 to 1.15), respectively. Conclusion: A well-structured education program has reduced both inter- and intraobserver prostate contouring variations. The impact was greater on MRI than on CT. With the ongoing incorporation of new technologies into routine practice, education programs for target contouring should be incorporated as part of the continuing medical education of radiation oncologists.

Dose calculation in patients undergoing radiotherapy treatments requires the knowledge of their anatomical geometry.Making reference to the specific case of breast cancer, one of the measurement that are made on the patients is the acquisition of the breast's contour, determined in an axial plane from a point marked on the breastbone until another point marked on the thorax side under the armpit.This measurement is normally made with a mechanic contour-meter: a device formed by a series of plastic-covered wires designed to be applied on the patient's skin copying the breast contour after it deformation.The geometrical error associated with this procedure is ± 1 cm. The precision of the dose calculation could be increased acquiring a breast contour more accurate.This objective was achieved developing a method based on breast images from a digital camera.The algorithms to obtain an axial-plane image of the contour from digital photographs taken from arbitrary positions were developed.A geometric transformation is applied to the photograph to correct for perspective distortions, obtaining a frontal - undistorted image (axial-plane image).A software tool to make all the image processing was developed under MatLab.The maximum geometrical error detected during the validation of the process was 2 mm [es

Methodology of analysis of stability is expounded to the one contour systems automatic control feedback in the presence of non-linearities. The methodology is based on the use of the simplest mathematical models of the nonlinear controllable systems. Stability of program manifolds of one contour automatic control systems is investigated. The sufficient conditions of program manifold's absolute stability of one contour automatic control systems are obtained. The Hurwitz's angle of absolute stability was determined. The sufficient conditions of program manifold's absolute stability of control systems by the course of plane in the mode of autopilot are obtained by means Lyapunov's second method.

Purpose: To determine if auto-contour and manual-contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT. Methods: Manual and auto-contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto-contouring was completed utilizing Pinnacle’s Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7-beam IMRT plans are created; PD with drawn ROIs, PAS with auto-contoured ROIs, and PM with auto-contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampled systematic errors for each simulation and a different sampled random error for each fraction were performed using our in-house GPU-accelerated robustness analyzer tool which reports the statistical probability of achieving dose-volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto-contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross-evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose-volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D-PD). Results: We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV’s D95 and Dmin objectives are small for AS-PM, AS-PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS-PM, AS-PD sustain variations up to %6 compared to other evaluated pairs. Conclusion: No significant probabilistic differences are observed in the metrics when auto-contoured OARs are used. The prostate auto-contour needs

Purpose: To determine if auto-contour and manual-contour—based plans differ when evaluated with respect to probabilistic coverage metrics and biological model endpoints for prostate IMRT. Methods: Manual and auto-contours were created for 149 CT image sets acquired from 16 unique prostate patients. A single physician manually contoured all images. Auto-contouring was completed utilizing Pinnacle’s Smart Probabilistic Image Contouring Engine (SPICE). For each CT, three different 78 Gy/39 fraction 7-beam IMRT plans are created; PD with drawn ROIs, PAS with auto-contoured ROIs, and PM with auto-contoured OARs with the manually drawn target. For each plan, 1000 virtual treatment simulations with different sampled systematic errors for each simulation and a different sampled random error for each fraction were performed using our in-house GPU-accelerated robustness analyzer tool which reports the statistical probability of achieving dose-volume metrics, NTCP, TCP, and the probability of achieving the optimization criteria for both auto-contoured (AS) and manually drawn (D) ROIs. Metrics are reported for all possible cross-evaluation pairs of ROI types (AS,D) and planning scenarios (PD,PAS,PM). Bhattacharyya coefficient (BC) is calculated to measure the PDF similarities for the dose-volume metric, NTCP, TCP, and objectives with respect to the manually drawn contour evaluated on base plan (D-PD). Results: We observe high BC values (BC≥0.94) for all OAR objectives. BC values of max dose objective on CTV also signify high resemblance (BC≥0.93) between the distributions. On the other hand, BC values for CTV’s D95 and Dmin objectives are small for AS-PM, AS-PD. NTCP distributions are similar across all evaluation pairs, while TCP distributions of AS-PM, AS-PD sustain variations up to %6 compared to other evaluated pairs. Conclusion: No significant probabilistic differences are observed in the metrics when auto-contoured OARs are used. The prostate auto-contour needs

INTRODUCTION: Body contouring surgery is associated with changes in body image and identity. The primary aim of the study was to investigate a multidisciplinary assessment of potential psychological challenges before and after body contouring surgery. METHODS: Eight pre- and post-operative patients...... relevant codes had been extracted. RESULTS: A total of seven psychological themes were iden- tified, indicating that surgery alone cannot improve the pa- tients’ psychological difficulties and that psychological care and management of the expected discomfort and body im- age is of considerable importance...... in providing continuity of care. CONCLUSIONS: The reported quality of life is of consider- able importance to patients undergoing body contouring surgery after massive weight loss. Our findings may provide useful information for surgeons and healthcare profes- sionals allowing them to develop patient education...

The watercolor effect is a long-range, assimilative, filling-in phenomenon induced by a pair of distant, wavy contours of different chromaticities. Here, we measured joint influences of the contour frequency and amplitude and the luminance of the interior contour on the strength of the effect. Contour pairs, each enclosing a circular region, were presented with two of the dimensions varying independently across trials (luminance/frequency, luminance/amplitude, frequency/amplitude) in a conjoint measurement paradigm (Luce & Tukey, 1964). In each trial, observers judged which of the stimuli evoked the strongest fill-in color. Control stimuli were identical except that the contours were intertwined and generated little filling-in. Perceptual scales were estimated by a maximum likelihood method (Ho, Landy, & Maloney, 2008). An additive model accounted for the joint contributions of any pair of dimensions. As shown previously using difference scaling (Devinck & Knoblauch, 2012), the strength increases with luminance of the interior contour. The strength of the phenomenon was nearly independent of the amplitude of modulation of the contour but increased with its frequency up to an asymptotic level. On average, the strength of the effect was similar along a given dimension regardless of the other dimension with which it was paired, demonstrating consistency of the underlying estimated perceptual scales.

Pervasive computing offers an unprecedented opportunity to unobtrusively monitor behavior and use the large amount of collected data to perform analysis of activity-based behavioral patterns. In this paper, we introduce the notion of an activity curve , which represents an abstraction of an individual's normal daily routine based on automatically-recognized activities. We propose methods to detect changes in behavioral routines by comparing activity curves and use these changes to analyze the possibility of changes in cognitive or physical health. We demonstrate our model and evaluate our change detection approach using a longitudinal smart home sensor dataset collected from 18 smart homes with older adult residents. Finally, we demonstrate how big data-based pervasive analytics such as activity curve-based change detection can be used to perform functional health assessment. Our evaluation indicates that correlations do exist between behavior and health changes and that these changes can be automatically detected using smart homes, machine learning, and big data-based pervasive analytics.

This report is a part of the reporting of the work done in the project `Active Control of Wind Turbines`. This project aim is to develop a simulation model for design of control systems for turbines with pitch control and to use that model to design controllers. This report describes the model developed for controller design and analysis. Emphasis has been put on establishment of simple models describing the dynamic behavior of the wind turbine in adequate details for controller design. This has been done with extensive use of measurements as the basis for selection of model complexity and model validation as well as parameter estimation. The model includes a simple model of the structure of the turbine including tower and flapwise blade bending, a detailed model of the gear box and induction generator, a linearized aerodynamic model including modelling of induction lag and actuator and sensor models. The models are all formulated as linear differential equations. The models are validated through comparisons with measurements performed on a Vestas WD 34 400 kW wind turbine. It is shown from a control point of view simple linear models can be used to describe the dynamic behavior of a pitch controlled wind turbine. The model and the measurements corresponds well in the relevant frequency range. The developed model is therefore applicable for controller design. (au) EFP-91. 18 ills., 22 refs.

Full Text Available Contour Crafting is a novel technology in construction industry based on 3D printing that uses robotics to construct free form building structures by repeatedly laying down layers of material such as concrete. It is actually an approach to scale up automatic fabrication from building small industrial parts to constructing buildings. However, there are little information about contour crafting (CC in current use; present paper aims to describe the operational steps of creating a whole building by the machine reviewing relevant literature. Furthermore, it will represent the advantages of CC usage compared to traditional construction methods, as well as its applicability in construction industry.

It was found that, in an isotropic coordinate system, the tunneling approach brings a factor of 1/2 for the Hawking temperature of a Schwarzschild black hole. In this paper, we address this kind of problem by studying the relation between the Hawking temperature and the deformation of the integral contour for the scalar and Dirac particles tunneling. We find that the correct Hawking temperature can be obtained exactly as long as the integral contour deformed corresponding to the radial coordinate transform if the transformation is a non-regular or zero function at the event horizon.

Purpose: Radiotherapy (RT) contours delineated either manually or semiautomatically require verification before clinical usage. Manual evaluation is very time consuming. A new integrated software tool using supervised pattern contour recognition was thus developed to facilitate this process. Methods: The contouring tool was developed using an object-oriented programming language C# and application programming interfaces, e.g. visualization toolkit (VTK). The C# language served as the tool design basis. The Accord.Net scientific computing libraries were utilized for the required statistical data processing and pattern recognition, while the VTK was used to build and render 3-D mesh models from critical RT structures in real-time and 360° visualization. Principal component analysis (PCA) was used for system self-updating geometry variations of normal structures based on physician-approved RT contours as a training dataset. The inhouse design of supervised PCA-based contour recognition method was used for automatically evaluating contour normality/abnormality. The function for reporting the contour evaluation results was implemented by using C# and Windows Form Designer. Results: The software input was RT simulation images and RT structures from commercial clinical treatment planning systems. Several abilities were demonstrated: automatic assessment of RT contours, file loading/saving of various modality medical images and RT contours, and generation/visualization of 3-D images and anatomical models. Moreover, it supported the 360° rendering of the RT structures in a multi-slice view, which allows physicians to visually check and edit abnormally contoured structures. Conclusion: This new software integrates the supervised learning framework with image processing and graphical visualization modules for RT contour verification. This tool has great potential for facilitating treatment planning with the assistance of an automatic contour evaluation module in avoiding

three minutes, the next press of any button marked the end of the experimental run , and triggered an acoustical signal. Time intervals for each of the...1955) Margini quasi-percettivi in campi con stimolazione omogenea. Rivista di Psicologia 49, 17-30. Lawson, R.B., Cowan, E., Gibbs, T.D. & Whitmore

Active Appearance Models (AAMs) are statistical models of shape and appearance widely used in computer vision to detect landmarks on objects like faces. Fitting an AAM to a new image can be formulated as a non-linear least-squares problem which is typically solved using iterative methods. Owing to

In this paper a didactical model is presented. The goal of the model is to work as a didactical tool, or conceptual frame, for developing, carrying through and evaluating interdisciplinary activities involving the subject of mathematics and philosophy in the high schools. Through the terms...... of Horizontal Intertwining, Vertical Structuring and Horizontal Propagation the model consists of three phases, each considering different aspects of the nature of interdisciplinary activities. The theoretical modelling is inspired by work which focuses on the students abilities to concept formation in expanded...... domains (Michelsen, 2001, 2005a, 2005b). Furthermore the theoretical description rest on a series of qualitative interviews with teachers from the Danish high school (grades 9-11) conducted recently. The special case of concrete interdisciplinary activities between mathematics and philosophy is also...

On the basis of the neurophysiological strength-duration (amplitude-duration) curve of neuron activation (which relates the threshold amplitude of a rectangular current pulse of neuron activation to the pulse duration), as well as with the use of activation energy constraint (the threshold curve corresponds to the energy threshold of neuron activation by a rectangular current pulse), an energy model of neuron activation by a single current pulse has been constructed. The constructed model of activation, which determines its spectral properties, is a bandpass filter. Under the condition of minimum-phase feature of the neuron activationmodel, on the basis of Hilbert transform, the possibilities of phase-frequency response calculation from its amplitude-frequency response have been considered. Approximation to the amplitude-frequency response by the response of the Butterworth filter of the first order, as well as obtaining the pulse response corresponding to this approximation, give us the possibility of analyzing the efficiency of activating current pulses of various shapes, including analysis in accordance with the energy constraint.

We study the problem of maintaining the contour tree T of a terrain Sigma, represented as a triangulated xy-monotone surface, as the heights of its vertices vary continuously with time. We characterize the combinatorial changes in T and how they relate to topological changes in Sigma. We present ...

We consider maintaining the contour tree T of a piecewise-linear triangulation M that is the graph of a time varying height function h:R2→R. We carefully describe the combinatorial change in T that happen as h varies over time and how these changes relate to topological changes in M. We present a...

SEM images provide valuable information about patterning capability. Geometrical properties such as Critical Dimension (CD) can be extracted from them and are used to calibrate OPC models, thus making OPC more robust and reliable. However, there is currently a shortage of appropriate metrology tools to inspect complex two-dimensional patterns in the same way as one would work with simple one-dimensional patterns. In this article we present a full framework for the analysis of SEM images. It has been proven to be fast, reliable and robust for every type of structure, and particularly for two-dimensional structures. To achieve this result, several innovative solutions have been developed and will be presented in the following pages. Firstly, we will present a new noise filter which is used to reduce noise on SEM images, followed by an efficient topography identifier, and finally we will describe the use of a topological skeleton as a measurement tool that can extend CD measurements on all kinds of patterns.

The purpose of this study was to determine whether contouring thoracic organs at risk was consistent among medical dosimetrists and to identify how trends in dosimetrist's education and experience affected contouring accuracy. Qualitative and quantitative methods were used to contextualize the raw data that were obtained. A total of 3 different computed tomography (CT) data sets were provided to medical dosimetrists (N = 13) across 5 different institutions. The medical dosimetrists were directed to contour the lungs, heart, spinal cord, and esophagus. The medical dosimetrists were instructed to contour in line with their institutional standards and were allowed to use any contouring tool or technique that they would traditionally use. The contours from each medical dosimetrist were evaluated against “gold standard” contours drawn and validated by 2 radiation oncology physicians. The dosimetrist-derived contours were evaluated against the gold standard using both a Dice coefficient method and a penalty-based metric scoring system. A short survey was also completed by each medical dosimetrist to evaluate their individual contouring experience. There was no significant variation in the contouring consistency of the lungs and spinal cord. Intradosimetrist contouring was consistent for those who contoured the esophagus and heart correctly; however, medical dosimetrists with a poor metric score showed erratic and inconsistent methods of contouring.

Intelligent (or smart) materials are increasingly becoming key materials for use in actuators and sensors. If an intelligent material is used as a sensor, it can be embedded in a variety of structure functioning as a health monitoring system to make their life longer with high reliability. If an intelligent material is used as an active material in an actuator, it plays a key role of making dynamic movement of the actuator under a set of stimuli. This talk intends to cover two different active materials in actuators, (1) piezoelectric laminate with FGM microstructure, (2) ferromagnetic shape memory alloy (FSMA). The advantage of using the FGM piezo laminate is to enhance its fatigue life while maintaining large bending displacement, while that of use in FSMA is its fast actuation while providing a large force and stroke capability. Use of hierarchical modeling of the above active materials is a key design step in optimizing its microstructure for enhancement of their performance. I will discuss briefly hierarchical modeling of the above two active materials. For FGM piezo laminate, we will use both micromechanical model and laminate theory, while for FSMA, the modeling interfacing nano-structure, microstructure and macro-behavior is discussed. (author)

U.S. Geological Survey, Department of the Interior — The USGS Elevation Contours service from The National Map (TNM) consists of contours generated for the conterminous United States from 1- and 1/3 arc-second...

In this paper, a new invariant feature of two-dimensional contours is reported: the Invariance Signature. The Invariance Signature is a measure of the degree to which a contour is invariant under a variety of transformations, derived from the theory of Lie transformation groups. It is shown that the Invariance Signature is itself invariant under shift, rotation and scaling of the contour. Since it is derived from local properties of the contour, it is well-suited to a neural network implement...

Noise pollution is an important factor in selecting suitable sites for wind turbines in order to realize 1000 MW of wind power as planned by the Dutch government for the year 2000. Therefore an accurate assessment of wind turbine noise is important. The amount of noise pollution from a wind turbine depends on the wind conditions. An existing standard method to assess wind turbine noise is supplemented and adjusted. In the first part of the investigation the method was developed and applied for a solitary sound source. In the second part attention is paid to the use of the method for wind turbine arrays. It appears that the adjusted method results in a shift of the contours of the permitted noise level. In general the contours are 15-25% closer to the wind farm, which means that the minimal permitted distance between houses and wind turbine arrays can be reduced. 14 figs., 1 tab., 4 appendices, 7 refs

A method and apparatus are provided for forming shapes and contours in metal sections by generating laser induced compressive stress on the surface of the metal workpiece. The laser process can generate deep compressive stresses to shape even thick components without inducing unwanted tensile stress at the metal surface. The precision of the laser-induced stress enables exact prediction and subsequent contouring of parts. A light beam of 10 to 100 J/pulse is imaged to create an energy fluence of 60 to 200 J/cm.sup.2 on an absorptive layer applied over a metal surface. A tamping layer of water is flowed over the absorptive layer. The absorption of laser light causes a plasma to form and consequently creates a shock wave that induces a deep residual compressive stress into the metal. The metal responds to this residual stress by bending.

Microgenetic analysis was used to investigate perception of illusory contour figures which represent whole, completed forms on the basis of segmented, incomplete stimulation. The analysis provided an experimental approach to this phenomenon which was standardly investigated phenomenologically. Experimental procedure consisted of two phases: a) priming phase and b) test phase which consisted of visual search task. Two types of visual search tasks were applied: (i) classic detection, in which s...

The contour method is becoming an increasingly popular measurement technique for mapping residual stress in engineering components. The accuracy of the technique is critically dependent on the quality of the cut performed. This paper presents results from blind cutting trials on austenitic stainless steel using electro-discharge machines made by three manufacturers. The suitability of the machines is assessed based on the surface finish achieved, risk of wire breakages and the nature of cutti...

To explore mechanisms of object integration, the present experiments examined how completion of illusory contours and surfaces modulates the sensitivity of localizing a target probe. Observers had to judge whether a briefly presented dot probe was located inside or outside the region demarcated by inducer elements that grouped to form variants of an illusory, Kanizsa-type figure. From the resulting psychometric functions, we determined observers' discrimination thresholds as a sensitivity measure. Experiment 1 showed that sensitivity was systematically modulated by the amount of surface and contour completion afforded by a given configuration. Experiments 2 and 3 presented stimulus variants that induced an (occluded) object without clearly defined bounding contours, which gave rise to a relative sensitivity increase for surface variations on their own. Experiments 4 and 5 were performed to rule out that these performance modulations were simply attributable to variable distances between critical local inducers or to costs in processing an interrupted contour. Collectively, the findings provide evidence for a dissociation between surface and contour processing, supporting a model of object integration in which completion is instantiated by feedforward processing that independently renders surface filling-in and contour interpolation and a feedback loop that integrates these outputs into a complete whole. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

We present an overview of various edge and line oriented approaches to contour detection that have been proposed in the last two decades. By edge and line oriented we mean methods that do not rely on segmentation. Distinction is made between edges and contours. Contour detectors are divided in local

Inspired by psychophysical studies of the human cognitive abilities we propose a novel aspect and a method for performance evaluation of contour based shape recognition algorithms regarding their robustness to incompleteness of contours. We use complete contour representations of objects as a

Full Text Available Gait recognition aims to identify people by the way they walk. In this paper, a simple but e ective gait recognition method based on Outermost Contour is proposed. For each gait image sequence, an adaptive silhouette extraction algorithm is firstly used to segment the frames of the sequence and a series of postprocessing is applied to obtain the normalized silhouette images with less noise. Then a novel feature extraction method based on Outermost Contour is performed. Principal Component Analysis (PCA is adopted to reduce the dimensionality of the distance signals derived from the Outermost Contours of silhouette images. Then Multiple Discriminant Analysis (MDA is used to optimize the separability of gait features belonging to di erent classes. Nearest Neighbor (NN classifier and Nearest Neighbor classifier with respect to class Exemplars (ENN are used to classify the final feature vectors produced by MDA. In order to verify the e ectiveness and robustness of our feature extraction algorithm, we also use two other classifiers: Backpropagation Neural Network (BPNN and Support Vector Machine (SVM for recognition. Experimental results on a gait database of 100 people show that the accuracy of using MDA, BPNN and SVM can achieve 97.67%, 94.33% and 94.67%, respectively.

Despite the increasing interest in mesotherapy as an alternative method for body contouring, there are few reports of its safety, efficacy, and mechanism of action. A clinical examination was performed to evaluate the efficacy of mesotherapy for body contouring. Twenty women were enrolled in this prospective, case-controlled study over a 12-week period. The authors injected a mixed solution (i.e., aminophylline, buflomedil, and lidocaine) into the superficial dermis of the medial aspect of one thigh weekly using a mechanical delivery gun. There was no treatment to the other thigh. The change in the fat level was evaluated by measuring the girth of the thighs and by computed tomographic scanning. The lipid profiles were checked to determine the effect of mesotherapy on lipid metabolism, and questionnaires were used to determine the satisfaction rate of the patients. The loss of thigh girth on the treated side was not significantly different from that of the untreated side. The computed tomographic scans showed no statistically significant difference in the cross-sectional area or thickness of the fat layer between each group. There were no statistically significant changes in the lipid profiles except for the triglyceride level. A questionnaire asking about the effect of mesotherapy indicated poor patient satisfaction. Mesotherapy is not an effective alternative treatment modality for body contouring.

Purpose: A system has been developed which recognizes and classifies Digital Imaging and Communication in Medicine contour data with minimal human intervention. It allows researchers to overcome obstacles which tax analysis and mining systems, including inconsistent naming conventions and differences in data age or resolution. Methods: Lexicographic and geometric analysis is used for recognition. Well-known lexicographic methods implemented include Levenshtein-Damerau, bag-of-characters, Double Metaphone, Soundex, and (word and character)-N-grams. Geometrical implementations include 3D Fourier Descriptors, probability spheres, boolean overlap, simple feature comparison (e.g. eccentricity, volume) and rule-based techniques. Both analyses implement custom, domain-specific modules (e.g. emphasis differentiating left/right organ variants). Contour labels from 60 head and neck patients are used for cross-validation. Results: Mixed-lexicographical methods show an effective improvement in more than 10% of recognition attempts compared with a pure Levenshtein-Damerau approach when withholding 70% of the lexicon. Domain-specific and geometrical techniques further boost performance. Conclusions: DICOMautomaton allows users to recognize contours semi-automatically. As usage increases and the lexicon is filled with additional structures, performance improves, increasing the overall utility of the system.

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model to address the problems of perceptual grouping and figure-ground segregation in vision. A novel feature is that the efficacy of the connections is allowed to change on a fast time scale. This results in active reentrant connections that amplify the correlations among neuronal groups. The responses of the model are able to link the elements corresponding to a coherent figure and to segregate them from the background or from another figure in a way that is consistent with the so-called Gestalt laws.

The segmentation of visual scenes is a fundamental process of early vision, but the underlying neural mechanisms are still largely unknown. Theoretical considerations as well as neurophysiological findings point to the importance in such processes of temporal correlations in neuronal activity. In a previous model, we showed that reentrant signaling among rhythmically active neuronal groups can correlate responses along spatially extended contours. We now have modified and extended this model to address the problems of perceptual grouping and figure-ground segregation in vision. A novel feature is that the efficacy of the connections is allowed to change on a fast time scale. This results in active reentrant connections that amplify the correlations among neuronal groups. The responses of the model are able to link the elements corresponding to a coherent figure and to segregate them from the background or from another figure in a way that is consistent with the so-called Gestalt laws.

The Institute of Nuclear Materials Management was founded and has grown on the basis of promoting professionalism in the nuclear industry. This paper is concerned with professional management of nuclear material. The paper introduces the reader to Emphasis, an active management model. The management model provides the framework to assist a manager in directing his available resources. Emphasis provides for establishing goals, identifying and selecting objectives, matching objectives to specific personnel, preparing and monitoring action plans, and evaluating results. The model stresses crisis prevention by systematically administering and controlling resources. A critical requirement for implementation of the model is the desire to manage, to be in charge of the situation. The nuclear industry does need managers - people who realize the sensitive nature of the industry, professionals who insist on improved performance

Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....

Full Text Available The membrane protein prestin is native to the cochlear outer hair cell that is crucial to the ear's amplification and frequency selectivity throughout the whole acoustic frequency range. The outer hair cell exhibits interrelated dimensional changes, force generation, and electric charge transfer. Cells transfected with prestin acquire unique active properties similar to those in the native cell that have also been useful in understanding the process. Here we propose a model describing the major electromechanical features of such active membranes. The model derived from thermodynamic principles is in the form of integral relationships between the history of voltage and membrane resultants as independent variables and the charge density and strains as dependent variables. The proposed model is applied to the analysis of an active force produced by the outer hair cell in response to a harmonic electric field. Our analysis reveals the mechanism of the outer hair cell active (isometric force having an almost constant amplitude and phase up to 80 kHz. We found that the frequency-invariance of the force is a result of interplay between the electrical filtering associated with prestin and power law viscoelasticity of the surrounding membrane. Paradoxically, the membrane viscoelasticity boosts the force balancing the electrical filtering effect. We also consider various modes of electromechanical coupling in membrane with prestin associated with mechanical perturbations in the cell. We consider pressure or strains applied step-wise or at a constant rate and compute the time course of the resulting electric charge. The results obtained here are important for the analysis of electromechanical properties of membranes, cells, and biological materials as well as for a better understanding of the mechanism of hearing and the role of the protein prestin in this mechanism.

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

Purpose: To predict voxel-level dose distribution and enable effective evaluation of cord dose sparing in spine SBRT. Methods: We present an active optical flow model (AOFM) to statistically describe cord dose variations and train a predictive model to represent correlations between AOFM and PTV contours. Thirty clinically accepted spine SBRT plans are evenly divided into training and testing datasets. The development of predictive model consists of 1) collecting a sequence of dose maps including PTV and OAR (spinal cord) as well as a set of associated PTV contours adjacent to OAR from the training dataset, 2) classifying data into five groups based on PTV's locations relative to OAR, two “Top”s, “Left”, “Right”, and “Bottom”, 3) randomly selecting a dose map as the reference in each group and applying rigid registration and optical flow deformation to match all other maps to the reference, 4) building AOFM by importing optical flow vectors and dose values into the principal component analysis (PCA), 5) applying another PCA to features of PTV and OAR contours to generate an active shape model (ASM), and 6) computing a linear regression model of correlations between AOFM and ASM.When predicting dose distribution of a new case in the testing dataset, the PTV is first assigned to a group based on its contour characteristics. Contour features are then transformed into ASM's principal coordinates of the selected group. Finally, voxel-level dose distribution is determined by mapping from the ASM space to the AOFM space using the predictive model. Results: The DVHs predicted by the AOFM-based model and those in clinical plans are comparable in training and testing datasets. At 2% volume the dose difference between predicted and clinical plans is 4.2±4.4% and 3.3±3.5% in the training and testing datasets, respectively. Conclusion: The AOFM is effective in predicting voxel-level dose distribution for spine SBRT. Partially supported by NIH

Vermont Center for Geographic Information — (Link to Metadata) ElevationContours_CN10T (10ft contours) was extracted from ElevationContours_CN2T (2ft contours), which was generated by USGS from the 2004...

Full Text Available Obesity is a global disease with epidemic proportions. Bariatric surgery or modified lifestyles go a long way in mitigating the vast weight gain. Patients following these interventions usually undergo massive weight loss. This results in redundant tissues in various parts of the body. Loose skin causes increased morbidity and psychological trauma. This demands various body contouring procedures that are usually excisional. These procedures are complex and part of a painstaking process that needs a committed patient and an industrious plastic surgeon. As complications in these patients can be quite frequent, both the patient and the surgeon need to be aware and willing to deal with them.

Motivation: Focal therapy is an emerging low-morbidity treatment option for low-intermediate risk prostate cancer; however, challenges remain in accurately delivering treatment to specified targets and determining treatment success. Registered multi-parametric magnetic resonance imaging (MPMRI) acquired before and after treatment can support focal therapy evaluation and optimization; however, contouring variability, when defining the prostate, the clinical target volume (CTV) and the ablation region in images, reduces the precision of quantitative image-based focal therapy evaluation metrics. To inform the interpretation and clarify the limitations of such metrics, we investigated inter-observer contouring variability and its impact on four metrics. Methods: Pre-therapy and 2-week-post-therapy standard-of-care MPMRI were acquired from 5 focal cryotherapy patients. Two clinicians independently contoured, on each slice, the prostate (pre- and post-treatment) and the dominant index lesion CTV (pre-treatment) in the T2-weighted MRI, and the ablated region (post-treatment) in the dynamic-contrast- enhanced MRI. For each combination of clinician contours, post-treatment images were registered to pre-treatment images using a 3D biomechanical-model-based registration of prostate surfaces, and four metrics were computed: the proportion of the target tissue region that was ablated and the target:ablated region volume ratio for each of two targets (the CTV and an expanded planning target volume). Variance components analysis was used to measure the contribution of each type of contour to the variance in the therapy evaluation metrics. Conclusions: 14-23% of evaluation metric variance was attributable to contouring variability (including 6-12% from ablation region contouring); reducing this variability could improve the precision of focal therapy evaluation metrics.

Contour integration is the joining-up of local responses to parts of a contour into a continuous percept. In typical studies observers detect contours formed of discrete wavelets, presented against a background of random wavelets. This measures performance for detecting contours in the limiting external noise that background provides. Our novel task measures contour integration without requiring any background noise. This allowed us to perform noise-masking experiments using orientation and position noise. From these we measure the equivalent internal noise for contour integration. We found an orientation noise of 6° and position noise of 3 arcmin. Orientation noise was 2.6x higher in contour integration compared to an orientation discrimination control task. Comparing against a position discrimination task found position noise in contours to be 2.4x lower. This suggests contour integration involves intermediate processing that enhances the quality of element position representation at the expense of element orientation. Efficiency relative to the ideal observer was lower for the contour tasks (36% in orientation noise, 21% in position noise) compared to the controls (54% and 57%).

Full Text Available The purpose of this paper to identify deviations fidelity spatial contours of industrial robots, determine the error pattern detected, and define the ways to solve the problem.The paper presents the research results of fidelity spatial contours done by Fanuc M- 710iC/50 industrial robot when moving along a predetermined path. The proposed method uses a QC20-W ballbar wireless system of Renishaw company, designed to diagnose the state of the measurement and playback linear and angular displacements of the CNC.The solutions to adapt the QC20-W ballbar system to the constructive peculiarities of industrial robots with five or more independently controlled axes are given. The stages of the preparation of diagnostic systems and software robot movements are described.According to study results of errors that arise while playing back the programmed motions of a fixed point of robot capture in three mutually perpendicular planes its practical accuracy has been defined when performing movements in a given region of the working area, thereby allowing us, eventually, to draw a conclusion on the possibility to use a robot in one technological process or another.The study has resulted in emerging the guidelines for the operation of industrial robots with five or more independently controlled axes. Using these guidelines enables us to increase the playback accuracy of the industrial robot to 0.01 mm.

Contours maps (such as topographic maps) compress the information of a function over a two-dimensional area into a discrete set of closed lines that connect points of equal value (isolines), striking a fine balance between expressiveness and cognitive simplicity. They allow humans to perform many common sense reasoning tasks about the underlying function (e.g. elevation).

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by impaired social interaction, atypical communication and a restricted repertoire of interests and activities. Altered sensory and perceptual experiences are also common, and a notable perceptual difference between individuals with ASD and controls is their superior performance in visual tasks where it may be beneficial to ignore global context. This superiority may be the result of atypical integrative processing. To explore this claim we investigated visual integration in adults with ASD (diagnosed with Asperger's Syndrome) using two psychophysical tasks thought to rely on integrative processing-collinear facilitation and contour integration. We measured collinear facilitation at different flanker orientation offsets and contour integration for both open and closed contours. Our results indicate that compared to matched controls, ASD participants show (i) reduced collinear facilitation, despite equivalent performance without flankers; and (ii) less benefit from closed contours in contour integration. These results indicate weaker visuospatial integration in adults with ASD and suggest that further studies using these types of paradigms would provide knowledge on how contextual processing is altered in ASD.

Full Text Available Autism spectrum disorder (ASD is a neurodevelopmental disorder characterized by impaired social interaction, atypical communication and a restricted repertoire of interests and activities. Altered sensory and perceptual experiences are also common, and a notable perceptual difference between individuals with ASD and controls is their superior performance in visual tasks where it may be beneficial to ignore global context. This superiority may be the result of atypical integrative processing. To explore this claim we investigated visual integration in adults with ASD (diagnosed with Asperger’s Syndrome using two psychophysical tasks thought to rely on integrative processing - collinear facilitation and contour integration. We measured collinear facilitation at different flanker orientation offsets and contour integration for both open and closed contours. Our results indicate that compared to matched controls, ASD participants show (i reduced collinear facilitation, despite equivalent performance without flankers and (ii less benefit from closed contours in contour integration. These results indicate weaker visuospatial integration in adults with ASD and suggest that further studies using these types of paradigms would provide knowledge on how contextual processing is altered in ASD.

Full Text Available Individuals with congenital amusia usually exhibit impairments in melodic contour processing when asked to compare pairs of melodies that may or may not be identical to one another. However, it is unclear whether the impairment observed in contour processing is caused by an impairment of pitch discrimination, or is a consequence of poor pitch memory. To help resolve this ambiguity, we designed a novel Self-paced Audio-visual Contour Task (SACT that evaluates sensitivity to contour while placing minimal burden on memory. In this task, participants control the pace of an auditory contour that is simultaneously accompanied by a visual contour, and they are asked to judge whether the two contours are congruent or incongruent. In Experiment 1, melodic contours varying in pitch were presented with a series of dots that varied in spatial height. Amusics exhibited reduced sensitivity to audio-visual congruency in comparison to control participants. To exclude the possibility that the impairment arises from a general deficit in cross-modal mapping, Experiment 2 examined sensitivity to cross-modal mapping for two other auditory dimensions: timbral brightness and loudness. Amusics and controls were significantly more sensitive to large than small contour changes, and to changes in loudness than changes in timbre. However, there were no group differences in cross-modal mapping, suggesting that individuals with congenital amusia can comprehend spatial representations of acoustic information. Taken together, the findings indicate that pitch contour processing in congenital amusia remains impaired even when pitch memory is relatively unburdened.

Individuals with congenital amusia usually exhibit impairments in melodic contour processing when asked to compare pairs of melodies that may or may not be identical to one another. However, it is unclear whether the impairment observed in contour processing is caused by an impairment of pitch discrimination, or is a consequence of poor pitch memory. To help resolve this ambiguity, we designed a novel Self-paced Audio-visual Contour Task (SACT) that evaluates sensitivity to contour while placing minimal burden on memory. In this task, participants control the pace of an auditory contour that is simultaneously accompanied by a visual contour, and they are asked to judge whether the two contours are congruent or incongruent. In Experiment 1, melodic contours varying in pitch were presented with a series of dots that varied in spatial height. Amusics exhibited reduced sensitivity to audio-visual congruency in comparison to control participants. To exclude the possibility that the impairment arises from a general deficit in cross-modal mapping, Experiment 2 examined sensitivity to cross-modal mapping for two other auditory dimensions: timbral brightness and loudness. Amusics and controls were significantly more sensitive to large than small contour changes, and to changes in loudness than changes in timbre. However, there were no group differences in cross-modal mapping, suggesting that individuals with congenital amusia can comprehend spatial representations of acoustic information. Taken together, the findings indicate that pitch contour processing in congenital amusia remains impaired even when pitch memory is relatively unburdened.

Full Text Available Introduction: The aim of this study was to evaluate the effect of proximal contour of class II composite restorations placed with straight or contoured matrix band using composite resins with different modulus of elasticity on stress distribution by finite element method. Methods: In order to evaluate the stress distribution of class II composite restorations using finite element method, upper right first molar and second premolar were modeled. Proximal boxes were designed and restored with universal Z250 and packable P60 composite resins (3M ESPE using two matrix systems: flat Tofflemire matrix and precurved sectional matrix. Finally models were evaluated under loads of 200 and 400 Newton at 90 degrees angle and the results were graphically illustrated in the form of Von Misses stresses. Results: In general the stress obtained under 400 Newton load was significantly greater than the stress of models under 200 Newton load. Von Misses stress distribution pattern of two different Z250 and P60 composites were very similar in all modes of loading and proximal contour. In all analyzed models there was a significant difference between models restored with Tofflemire matrix with flat contour and models restored with sectional matrix with curved contour. This difference was greater in first molar than second premolar. Conclusion: Use of a contoured matrix band results in less stress in class II composite resin restorations.

The processing of a visual stimulus can be subdivided into a number of stages. Upon stimulus presentation there is an early phase of feedforward processing where the visual information is propagated from lower to higher visual areas for the extraction of basic and complex stimulus features. This is followed by a later phase where horizontal connections within areas and feedback connections from higher areas back to lower areas come into play. In this later phase, image elements that are behaviorally relevant are grouped by Gestalt grouping rules and are labeled in the cortex with enhanced neuronal activity (object-based attention in psychology). Recent neurophysiological studies revealed that reward-based learning influences these recurrent grouping processes, but it is not well understood how rewards train recurrent circuits for perceptual organization. This paper examines the mechanisms for reward-based learning of new grouping rules. We derive a learning rule that can explain how rewards influence the information flow through feedforward, horizontal and feedback connections. We illustrate the efficiency with two tasks that have been used to study the neuronal correlates of perceptual organization in early visual cortex. The first task is called contour-integration and demands the integration of collinear contour elements into an elongated curve. We show how reward-based learning causes an enhancement of the representation of the to-be-grouped elements at early levels of a recurrent neural network, just as is observed in the visual cortex of monkeys. The second task is curve-tracing where the aim is to determine the endpoint of an elongated curve composed of connected image elements. If trained with the new learning rule, neural networks learn to propagate enhanced activity over the curve, in accordance with neurophysiological data. We close the paper with a number of model predictions that can be tested in future neurophysiological and computational studies

In the interest of enhancing the capabilities of autonomous underwater vehicles used in US Naval Operations, controlling vehicle position to follow depth contours presents exciting potential for navigation...

Contour plotting programs for plotting contour diagrams on printers or Calcomp plotters are described. The subroutines also exist in versions that are useful for the special application of finding minima and saddlepoints of nuclear potential energy surfaces generated by the subroutine PETR3 of another program package. For the general user, however, the most interesting aspect of the plotting package is probably the possibility of generating printer contour plots. The plotting of printer contour plots is a very fast and convenient way of displaying two-dimensional functions. 3 figures

Full Text Available Methodology of analysis of stability is expounded to the one contour systems automatic control feedback in the presence of non-linearities. The methodology is based on the use of the simplest mathematical models of the nonlinear controllable systems. Stability of program manifolds of one contour automatic control systems is investigated. The sufficient conditions of program manifold’s absolute stability of one contour automatic control systems are obtained. The Hurwitz’s angle of absolute stability was determined. The sufficient conditions of program manifold’s absolute stability of control systems by the course of plane in the mode of autopilot are obtained by means Lyapunov’s second method.

Full Text Available Even after about 70 years of separation, India and Pakistan continue to live in the prison of the past. The rhetoric of partition is still alive in the memory of the people of both the countries. They have constructed fixed, unchanging and competing images for each other. While Pakistan became an Islamic Republic, India adopted secularism, thereby, negating the two-nation theory. The ‘differences’ along with memories of partition has made Indian and Pakistani to remain in permanent hostile situation. The leaders of the two countries try to settle their disputes but fails because of lack of support from their social and political institutions. Since its coming into power in 2014, the NDA government under the Indian Prime Minister, Mr. Narendra Modi has managed to engage the Pakistani establishment, despite many problems between the two countries. This article tries to highlight upon the contours of relationships post-2014.

Full Text Available Aim: To develop a method for automatic contour extraction from a 2D image. Material and Method: The method is divided in two basic parts where the user initially chooses the starting point and the threshold. Finally the method is applied to computed tomography of bone images. Results: An interesting method is developed which can lead to a successful boundary extraction of 2D images. Specifically data extracted from a computed tomography images can be used for 2D bone reconstruction. Conclusions: We believe that such an algorithm or part of it can be applied on several other applications for shape feature extraction in medical image analysis and generally at computer graphics.

Imitating the signal acquisition and processing of vertebrate retina, a CMOS image sensor with bionic pre-processing circuit is designed. Integration of signal-process circuit on-chip can reduce the requirement of bandwidth and precision of the subsequent interface circuit, and simplify the design of the computer-vision system. This signal pre-processing circuit consists of adaptive photoreceptor, spatial filtering resistive network and Op-Amp calculation circuit. The adaptive photoreceptor unit with a dynamic range of approximately 100 dB has a good self-adaptability for the transient changes in light intensity instead of intensity level itself. Spatial low-pass filtering resistive network used to mimic the function of horizontal cell, is composed of the horizontal resistor (HRES) circuit and OTA (Operational Transconductance Amplifier) circuit. HRES circuit, imitating dendrite of the neuron cell, comprises of two series MOS transistors operated in weak inversion region. Appending two diode-connected n-channel transistors to a simple transconductance amplifier forms the OTA Op-Amp circuit, which provides stable bias voltage for the gate of MOS transistors in HRES circuit, while serves as an OTA voltage follower to provide input voltage for the network nodes. The Op-Amp calculation circuit with a simple two-stage Op-Amp achieves the image contour enhancing. By adjusting the bias voltage of the resistive network, the smoothing effect can be tuned to change the effect of image's contour enhancement. Simulations of cell circuit and 16×16 2D circuit array are implemented using CSMC 0.5μm DPTM CMOS process.

Purpose: To improve the accuracy of automatically segmented prostate, rectum, and bladder contours required for online adaptive therapy. The contouring accuracy on the current image guidance [image guided radiation therapy (IGRT)] scan is improved by combining contours from earlier IGRT scans via the simultaneous truth and performance level estimation (STAPLE) algorithm. Methods: Six IGRT prostate patients treated with daily kilo-voltage (kV) cone-beam CT (CBCT) had their original plan CT and nine CBCTs contoured by the same physician. Three types of automated contours were produced for analysis. (1) Plan: By deformably registering the plan CT to each CBCT and then using the resulting deformation field to morph the plan contours to match the CBCT anatomy. (2) Previous: The contour set drawn by the physician on the previous day CBCT is similarly deformed to match the current CBCT anatomy. (3) STAPLE: The contours drawn by the physician, on each prior CBCT and the plan CT, are deformed to match the CBCT anatomy to produce multiple contour sets. These sets are combined using the STAPLE algorithm into one optimal set. Results: Compared to plan and previous, STAPLE improved the average Dice's coefficient (DC) with the original physician drawn CBCT contours to a DC as follows: Bladder: 0.81 ± 0.13, 0.91 ± 0.06, and 0.92 ± 0.06; Prostate: 0.75 ± 0.08, 0.82 ± 0.05, and 0.84 ± 0.05; and Rectum: 0.79 ± 0.06, 0.81 ± 0.06, and 0.85 ± 0.04, respectively. The STAPLE results are within intraobserver consistency, determined by the physician blindly recontouring a subset of CBCTs. Comparing plans recalculated using the physician and STAPLE contours showed an average disagreement less than 1% for prostate D98 and mean dose, and 5% and 3% for bladder and rectum mean dose, respectively. One scan takes an average of 19 s to contour. Using five scans plus STAPLE takes less than 110 s on a 288 core graphics processor unit. Conclusions: Combining the plan and all prior days via

The Pilot Approximation Trajectory (PAT) contour algorithm can find the contour of a function accurately when it is not practical to evaluate the function on a grid dense enough to use a standard contour algorithm, for instance, when evaluating the function involves conducting a physical experiment or a computationally intensive simulation. PAT relies on an inexpensive pilot approximation to the function, such as interpolating from a sparse grid of inexact values, or solving a partial differential equation (PDE) numerically using a coarse discretization. For each level of interest, the location and ‘trajectory’ of an approximate contour of this pilot function are used to decide where to evaluate the original function to find points on its contour. Those points are joined by line segments to form the PAT approximation of the contour of the original function. Approximating a contour numerically amounts to estimating a lower level set of the function, the set of points on which the function does not exceed the contour level. The area of the symmetric difference between the true lower level set and the estimated lower level set measures the accuracy of the contour. PAT measures its own accuracy by finding an upper confidence bound for this area. In examples, PAT can estimate a contour more accurately than standard algorithms, using far fewer function evaluations than standard algorithms require. We illustrate PAT by constructing a confidence set for viscosity and thermal conductivity of a flowing gas from simulated noisy temperature measurements, a problem in which each evaluation of the function to be contoured requires solving a different set of coupled nonlinear PDEs. (paper)

Delineating regions of interest (ROIs) on each phase of four-dimensional (4D) computed tomography (CT) images is an essential step for 4D radiotherapy. The requirement of manual phase-by-phase contouring prohibits the routine use of 4D radiotherapy. This paper develops an automatic re-contouring algorithm that combines techniques of deformable registration and surface construction. ROIs are manually contoured slice-by-slice in the reference phase image. A reference surface is constructed based on these reference contours using a triangulated surface construction technique. The deformable registration technique provides the voxel-to-voxel mapping between the reference phase and the test phase. The vertices of the reference surface are displaced in accordance with the deformation map, resulting in a deformed surface. The new contours are reconstructed by cutting the deformed surface slice-by-slice along the transversal, sagittal or coronal direction. Since both the inputs and outputs of our automatic re-contouring algorithm are contours, it is relatively easy to cope with any treatment planning system. We tested our automatic re-contouring algorithm using a deformable phantom and 4D CT images of six lung cancer patients. The proposed algorithm is validated by visual inspections and quantitative comparisons of the automatic re-contours with both the gold standard segmentations and the manual contours. Based on the automatic delineated ROIs, changes of tumour and sensitive structures during respiration are quantitatively analysed. This algorithm could also be used to re-contour daily images for treatment evaluation and adaptive radiotherapy

The possibility of applying the mathematical formalism of spiral light beams to the problems of contour image recognition is theoretically studied. The advantages and disadvantages of the proposed approach are evaluated; the results of numerical modelling are presented. (optical image processing)

We present a system for detecting the pose of rigid objects using texture and contour information. From a stereo image view of a scene, a sparse hierarchical scene representation is reconstructed using an early cognitive vision system. We define an object model in terms of a simple context...

Shadow and projection moiré are the oldest forms of moiré to be used in actual technical applications. In spite of this fact and the extensive number of papers that have been published on this topic, the use of shadow moiré as an accurate tool that can compete with alternative devices poses very many problems that go to the very essence of the mathematical models used to obtain contour information from fringe pattern data. In this paper some recent developments on the projection moiré method are presented. Comparisons between the results obtained with the projection method and the results obtained by mechanical devices that operate with contact probes are presented. These results show that the use of projection moiré makes it possible to achieve the same accuracy that current mechanical touch probe devices can provide.

On average, we urban dwellers spend about 90% of our time indoors, and share the intuition that the physical features of the places we live and work in influence how we feel and act. However, there is surprisingly little research on how architecture impacts behavior, much less on how it influences brain function. To begin closing this gap, we conducted a functional magnetic resonance imaging study to examine how systematic variation in contour impacts aesthetic judgments and approach-avoidance decisions, outcome measures of interest to both architects and users of spaces alike. As predicted, participants were more likely to judge spaces as beautiful if they were curvilinear than rectilinear. Neuroanatomically, when contemplating beauty, curvilinear contouractivated the anterior cingulate cortex exclusively, a region strongly responsive to the reward properties and emotional salience of objects. Complementing this finding, pleasantness—the valence dimension of the affect circumplex—accounted for nearly 60% of the variance in beauty ratings. Furthermore, activation in a distributed brain network known to underlie the aesthetic evaluation of different types of visual stimuli covaried with beauty ratings. In contrast, contour did not affect approach-avoidance decisions, although curvilinear spaces activated the visual cortex. The results suggest that the well-established effect of contour on aesthetic preference can be extended to architecture. Furthermore, the combination of our behavioral and neural evidence underscores the role of emotion in our preference for curvilinear objects in this domain. PMID:23754408

A necessary input to planet occurrence calculations is an accurate model for the pipeline completeness (Burke et al., 2015). This document describes the use of the Kepler planet occurrence rate products in order to calculate a per-target detection contour for the measured Data Release 25 (DR25) pipeline performance. A per-target detection contour measures for a given combination of orbital period, Porb, and planet radius, Rp, what fraction of transit signals are recoverable by the Kepler pipeline (Twicken et al., 2016; Jenkins et al., 2017). The steps for calculating a detection contour follow the procedure outlined in Burke et al. (2015), but have been updated to provide improved accuracy enabled by the substantially larger database of transit injection and recovery tests that were performed on the final version (i.e., SOC 9.3) of the Kepler pipeline (Christiansen, 2017; Burke Catanzarite, 2017a). In the following sections, we describe the main inputs to the per-target detection contour and provide a worked example of the python software released with this document (Kepler Planet Occurrence Rate Tools KeplerPORTs)1 that illustrates the generation of a detection contour in practice. As background material for this document and its nomenclature, we recommend the reader be familiar with the previous method of calculating a detection contour (Section 2 of Burke et al.,2015), input parameters relevant for describing the data quantity and quality of Kepler targets (Burke Catanzarite, 2017b), and the extensive new transit injection and recovery tests of the Kepler pipeline (Christiansen et al., 2016; Burke Catanzarite, 2017a; Christiansen, 2017).

We are developing a computerized method for bladder segmentation in CT urography (CTU) for computeraided diagnosis of bladder cancer. A challenge for computerized bladder segmentation in CTU is that the bladder often contains regions filled with intravenous (IV) contrast and without contrast. Previously, we proposed a Conjoint Level set Analysis and Segmentation System (CLASS) consisting of four stages: preprocessing and initial segmentation, 3D and 2D level set segmentation, and post-processing. In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast (C) filled region separately and conjoins the contours with a Contour Conjoint Procedure (CCP). The CCP is not trivial. Inaccuracies in the NC and C contours may cause CCP to exclude portions of the bladder. To alleviate this problem, we implemented model-guided refinement to propagate the C contour if the level set propagation in the region stops prematurely due to substantial non-uniformity of the contrast. An enhanced CCP with regularized energies further propagates the conjoint contours to the correct bladder boundary. Segmentation performance was evaluated using 70 cases. For all cases, 3D hand segmented contours were obtained as reference standard, and computerized segmentation accuracy was evaluated in terms of average volume intersection %, average % volume error, and average minimum distance. With enhanced CCP, those values were 84.4±10.6%, 8.3±16.1%, 3.4±1.8 mm, respectively. With CLASS, those values were 74.6±13.1%, 19.6±18.6%, 4.4±2.2 mm, respectively. The enhanced CCP improved bladder segmentation significantly (p<0.001) for all three performance measures.

This paper demonstrates the feasibility of a new method of hand-geometry recognition based on parameters derived from the contour of the hand. The contour is completely determined by the black-and-white image of the hand and can be derived from it by means of simple image-processing techniques. It

We consider the problem of detecting object contours in natural images. In many cases, local luminance changes turn out to be stronger in textured areas than on object contours. Therefore, local edge features, which only look at a small neighborhood of each pixel, cannot be reliable indicators of

Full Text Available A new programming method has been developed for grinding robots. Instead of using the conventional jog-and-teach method, the workpiece contour is automatically tracked by the robot. During the tracking, the robot position is stored in the robot control system every 8th millisecond. After filtering and reducing this contour data, a robot program is automatically generated.

A new programming method has been developed for grinding robots. Instead of using the conventional jog-and-teach method, the workpiece contour is automatically tracked by the robot. During the tracking, the robot position is stored in the robot control system every 8th millisecond. After filtering and reducing this contour data, a robot program is automatically generated.

The residual stresses formed as a result of Electronic Beam welding (EB-welding) in copper are investigated by Posiva. In the present study, residual stresses of EB-welded copper plates were studied with contour method. In the method eleven copper plates (X436 - X440 and X453 - X458) were cut in half with wire electric discharge machining (EDM) after which the deformation due to stress relaxation was measured with coordinate measurement system. The measured data was then used as boundary displacement data for the FEM analyses, in which the corresponding residual stresses were calculated. Before giving the corresponding displacement boundary conditions to the FE models, the deformation data was processed and smoothed appropriately. The residual stress levels of the copper plates were found to be around 40 - 55 MPa at maximum. This corresponds to other reported residual stress measurements and current state of knowledge with this material in Posiva. (orig.)

Purpose: To evaluate the correlation between image features and the accuracy of manually drawn target contours on synthetic PET images Methods: A digital PET phantom was used in combination with Monte Carlo simulation to create a set of 26 simulated PET images featuring a variety of tumor shapes and activity heterogeneity. These tumor volumes were used as a gold standard in comparisons with manual contours delineated by 10 radiation oncologist on the simulated PET images. Metrics used to evaluate segmentation accuracy included the dice coefficient, false positive dice, false negative dice, symmetric mean absolute surface distance, and absolute volumetric difference. Image features extracted from the simulated tumors consisted of volume, shape complexity, mean curvature, and intensity contrast along with five texture features derived from the gray-level neighborhood difference matrices including contrast, coarseness, busyness, strength, and complexity. Correlation between these features and contouring accuracy were examined. Results: Contour accuracy was reasonably well correlated with a variety of image features. Dice coefficient ranged from 0.7 to 0.90 and was correlated closely with contrast (r=0.43, p=0.02) and complexity (r=0.5, p<0.001). False negative dice ranged from 0.10 to 0.50 and was correlated closely with contrast (r=0.68, p<0.001) and complexity (r=0.66, p<0.001). Absolute volumetric difference ranged from 0.0002 to 0.67 and was correlated closely with coarseness (r=0.46, p=0.02) and complexity (r=0.49, p=0.008). Symmetric mean absolute difference ranged from 0.02 to 1 and was correlated closely with mean curvature (r=0.57, p=0.02) and contrast (r=0.6, p=0.001). Conclusion: The long term goal of this study is to assess whether contouring variability can be reduced by providing feedback to the practitioner based on image feature analysis. The results are encouraging and will be used to develop a statistical model which will enable a prediction of

The development of generalized contour/texture discrimination techniques is a central element necessary for machine vision recognition and interpretation of arbitrary images. Here, the visual perception of texture, selected studies of texture analysis in machine vision, and diverse small samples of contour and texture are all used to provide insights into the fundamental characteristics of contour and texture. From these, an experimental discrimination scheme is developed and tested on a battery of natural images. The visual perception of texture defined fine texture as a subclass which is interpreted as shading and is distinct from coarse figural similarity textures. Also, perception defined the smallest scale for contour/texture discrimination as eight to nine visual acuity units. Three contour/texture discrimination parameters were found to be moderately successful for this scale discrimination: (1) lightness change in a blurred version of the image, (2) change in lightness change in the original image, and (3) percent change in edge counts relative to local maximum.

one dimension that has recently been studied in the computer science community. The model involves movement with a speed proportional to a “fear...more realistic model of human locomotion. The movement of the criminal agents follows a biased Levy flight with step sizes distributed according to a...power-law distribution. The biased Brownian motion of the original model is then derived as a special case. Starting with an agent-based model, we

Full Text Available Microgenetic analysis was used to investigate perception of illusory contour figures which represent whole, completed forms on the basis of segmented, incomplete stimulation. The analysis provided an experimental approach to this phenomenon which was standardly investigated phenomenologically. Experimental procedure consisted of two phases: a priming phase and b test phase which consisted of visual search task. Two types of visual search tasks were applied: (i classic detection, in which subjects were detecting presence or absence of the target stimuli and (ii two-alternative forced choice, 2AFC, in which subjects performed discrimination between two concurrent targets (target A vs. target B. Variation of exposition of prim stimuli was used as an indication of the percept formation period. Concepts like early vision, visual attention and feature binding were investigated. Four experiments were conducted. Their outcome showed that (i perception of amodal figure requires visual attention, (ii features binding precedes spatial attention and (iii time period of percept formation is dependent of task properties and varies between 50 - 150 ms. Some results obtained in this research could be explained by feature-integration theory (Treisman & Gelade, 1980; Treisman, 1986. Furthermore, percept formation period data comply with data acquired in Elliott & Müller's psychophysical research (1998.

Full Text Available In today's busy world, most patients do not have time for long, drawn-out dental treatment. The time span between extraction and healing after loss of tooth in the anterior esthetic zone can be esthetically and psychologically devastating on the part of the patient. Especially, when a maxillary anterior tooth must be extracted and replaced, immediate tooth replacement with an ovate pontic on a provisional bridge is a good alternative. Ovate pontic helps in preservation of the interdental papilla, which in turn preserves the natural gingival contour that would have otherwise been lost after extraction. An immediate tooth replacement using ovate pontic not only eliminates the psychologically disturbing partially edentulous phase but also results in a much more esthetically pleasing replacement of tooth that is both hygienic and natural in appearance. Another added advantage of the use of ovate pontic is that it rules out the dissatisfaction resulting from an unesthetic ridge lap pontic placed directly over edentulous ridge. Just like the long-lived bird “Phoenix,” arising out of its own ashes, the ovate pontic creates an illusion that the pontic is emerging from the gingiva, even after tooth loss. This case report discusses how an integrated approach of fabricating heat cure provisional bridge with ovate pontics before extractions, benefitted a young patient in whom fractured anterior teeth were proposed for extraction.

CADx systems have the potential to support radiologists in the difficult task of discriminating benign and malignant mammographic lesions. The segmentation of mammographic masses from the background tissue is an important module of CADx systems designed for the characterization of mass lesions. In this work, a novel approach to this task is presented. The segmentation is performed by automatically tracing the mass' contour in-between manually provided landmark points defined on the mass' margin. The performance of the proposed approach is compared to the performance of implementations of three state-of-the-art approaches based on region growing and dynamic programming. For an unbiased comparison of the different segmentation approaches, optimal parameters are selected for each approach by means of tenfold cross-validation and a genetic algorithm. Furthermore, segmentation performance is evaluated on a dataset of ROI and ground-truth pairs. The proposed method outperforms the three state-of-the-art methods. The benchmark dataset will be made available with publication of this paper and will be the first publicly available benchmark dataset for mass segmentation.

Color induction was measured using a matching method for two spatial patterns, each composed of double contours. In one pattern (the standard), the contours had sharp edges to induce the Watercolor Effect (WCE); in the other, the two contours had a spatial taper so that the overall profile produced a sawtooth edge, or ramped stimulus. These patterns were chosen based on our previous study demonstrating that the strength of the chromatic WCE depends on a luminance difference between the two contours. Low-pass chromatic mechanisms, unlike bandpass luminance mechanisms, may be expected to be insensitive to the difference between the two spatial profiles. The strength of the watercolor spreading was similar for the two patterns at narrow widths of the contour possibly because of chromatic aberration, but with wider contours, the standard stimulus produced stronger assimilation than the ramped stimulus. This research suggests that luminance-dependent chromatic mechanisms mediate the WCE and that these mechanisms are sensitive to differences in the two spatial profiles of the pattern contours only when they are wide.

This paper presents a novel method to generate contour lines from grid DEM data based on the programmable GPU pipeline. The previous contouring approaches often use CPU to construct a finite element mesh from the raw DEM data, and then extract contour segments from the elements. They also need a tracing or sorting strategy to generate the final continuous contours. These approaches can be heavily CPU-costing and time-consuming. Meanwhile the generated contours would be unsmooth if the raw data is sparsely distributed. Unlike the CPU approaches, we employ the GPU's vertex shader to generate a triangular mesh with arbitrary user-defined density, in which the height of each vertex is calculated through a third-order Cardinal spline function. Then in the same frame, segments are extracted from the triangles by the geometry shader, and translated to the CPU-side with an internal order in the GPU's transform feedback stage. Finally we propose a "Grid Sorting" algorithm to achieve the continuous contour lines by travelling the segments only once. Our method makes use of multiple stages of GPU pipeline for computation, which can generate smooth contour lines, and is significantly faster than the previous CPU approaches. The algorithm can be easily implemented with OpenGL 3.3 API or higher on consumer-level PCs.

Full Text Available Standard edge detectors react to all local luminance changes, irrespective of whether they are due to the contours of the objects represented in a scene or due to natural textures like grass, foliage, water, and so forth. Moreover, edges due to texture are often stronger than edges due to object contours. This implies that further processing is needed to discriminate object contours from texture edges. In this paper, we propose a biologically motivated multiresolution contour detection method using Bayesian denoising and a surround inhibition technique. Specifically, the proposed approach deploys computation of the gradient at different resolutions, followed by Bayesian denoising of the edge image. Then, a biologically motivated surround inhibition step is applied in order to suppress edges that are due to texture. We propose an improvement of the surround suppression used in previous works. Finally, a contour-oriented binarization algorithm is used, relying on the observation that object contours lead to long connected components rather than to short rods obtained from textures. Experimental results show that our contour detection method outperforms standard edge detectors as well as other methods that deploy inhibition.

Full Text Available Contour integration is a fundamental visual process. The constraints on integrating discrete contour elements and the associated neural mechanisms have typically been investigated using static contour paths. However, in our dynamic natural environment objects and scenes vary over space and time. With the aim of investigating the parameters affecting spatiotemporal contour path integration, we measured human contrast detection performance of a briefly presented foveal target embedded in dynamic collinear stimulus sequences (comprising five short 'predictor' bars appearing consecutively towards the fovea, followed by the 'target' bar in four experiments. The data showed that participants' target detection performance was relatively unchanged when individual contour elements were separated by up to 2° spatial gap or 200 ms temporal gap. Randomising the luminance contrast or colour of the predictors, on the other hand, had similar detrimental effect on grouping dynamic contour path and subsequent target detection performance. Randomising the orientation of the predictors reduced target detection performance greater than introducing misalignment relative to the contour path. The results suggest that the visual system integrates dynamic path elements to bias target detection even when the continuity of path is disrupted in terms of spatial (2°, temporal (200 ms, colour (over 10 colours and luminance (-25% to 25% information. We discuss how the findings can be largely reconciled within the functioning of V1 horizontal connections.

Radiation therapy treatment verification can be performed using hard copy portal films or digital Electronic Portal Images (EPI) of the treatment field, acquired at the time of treatment. This paper describes a practical method of assessing the accuracy of reference anatomy outlining, for treatment sites involving the pelvis, breast and lumbar spine. Seven original bone anatomy outlines contoured onto verification images of five patients, were printed on transparency sheets and reference points were marked at equal distances along the anatomy curves. Two sample anatomy contour sets were created by two independent radiation therapists who outlined visible bone anatomy on the same seven digitally reconstructed radiographs (DRR) and hard copy outlines were obtained. Three independent observers with differing levels of experience, assessed the discrepancies between the original anatomy contours and the sample sets on two occasions one week apart, by measuring the distances between the original and sample set contours (absolute values in mm). The degree of agreement between the same assessor on two occasions (intra-rater reliability) and between assessors (inter-rater reliability) was analysed using parametric analysis for levels of relationship and significant differences. This simple method of reference anatomy outline measurement was shown to be highly reliable within assessors and between assessors (r > 0.87 and rz > 0.75 for both intra- and inter-rater comparisons). This measurement process may be a suitable method, for undertaking quality assurance activities in image verification within radiation therapy departments. Copyright (2004) Australian Institute of Radiography

Among the visual preferences that guide many everyday activities and decisions, from consumer choices to social judgment, preference for curved over sharp-angled contours is commonly thought to have played an adaptive role throughout human evolution, favoring the avoidance of potentially harmful objects. However, because nonhuman primates also exhibit preferences for certain visual qualities, it is conceivable that humans' preference for curved contours is grounded on perceptual and cognitive mechanisms shared with extant nonhuman primate species. Here we aimed to determine whether nonhuman great apes and humans share a visual preference for curved over sharp-angled contours using a 2-alternative forced choice experimental paradigm under comparable conditions. Our results revealed that the human group and the great ape group indeed share a common preference for curved over sharp-angled contours, but that they differ in the manner and magnitude with which this preference is expressed behaviorally. These results suggest that humans' visual preference for curved objects evolved from earlier primate species' visual preferences, and that during this process it became stronger, but also more susceptible to the influence of higher cognitive processes and preference for other visual features.

Abstract. Perceived occlusion at T-junctions or illusory contours at implicit T-junctions are often modelled by using edge information without surface context. We explored the effect of closure on perceived occlusion at T-junctions. Two vertical lines separated by a gap each had six abutting horizontal lines on opposite sides forming T-junctions. These lines were either closed or not closed into pairs at the stem ends of the Ts. In experiment 1, closed T-junction stems gave a much stronger sense of occlusion at the vertical lines than unclosed ones, even though closure information was remote from the putative occlusion and local T-junction information remained constant. When the outer two T-junctions were converted to L-junctions, perceived occlusion considerably diminished. The effect of closure on illusory-contour strength for stimuli like those of experiment 1 but with the vertical lines omitted was explored in experiment 2. The two sets of horizontal lines, separated by a gap, were either closed or not closed into pairs at their outer ends. Illusory-contour strength along the vertical alignments was much greater for closed pairs. Line terminations on both sides of the gap enhanced illusory-contour strength, but whether they were collinear or not had little effect.

As design pitch shrinks to the resolution limit of up-to-date optical lithography technology, the Critical Dimension (CD) variation tolerance has been dramatically decreased for ensuring the functionality of device. One of critical challenges associates with the narrower CD tolerance for whole chip area is the proximity effect control on asymmetrical layout environments. To fulfill the tight CD control of complex features, the Critical Dimension Scanning Electron Microscope (CD-SEM) based measurement results for qualifying process window and establishing the Optical Proximity Correction (OPC) model become insufficient, thus 2D contour extraction technique [1-5] has been an increasingly important approach for complementing the insufficiencies of traditional CD measurement algorithm. To alleviate the long cycle time and high cost penalties for product verification, manufacturing requirements are better to be well handled at design stage to improve the quality and yield of ICs. In this work, in-house 2D contour extraction platform was established for layout design optimization of 39nm half-pitch Self-Aligned Double Patterning (SADP) process layer. Combining with the adoption of Process Variation Band Index (PVBI), the contour extraction platform enables layout optimization speedup as comparing to traditional methods. The capabilities of identifying and handling lithography hotspots in complex layout environments of 2D contour extraction platform allow process window aware layout optimization to meet the manufacturing requirements.

Full Text Available Based on the analysis results from the patent search and review of domestic and foreign publications in variable cycle engines (VCE was created a classification of the possible schematic diagrams of VCE realizing three-stream engine technologies (the adaptive low pressure compressor (LPC with air extraction behind stages, FLADE compressor, various feeding types of extraction air to the flowing path of the engine, etc..To estimate a three-stream engine application as a part of the power-plant (PP efficiency, was chosen an adaptive LPC technology scheme with the third contour air bypass beyond the critical section of a basic jet nozzle for which a mathematical model (MM of the PP has been created on the basis of one-dimensional MM of the engine. The MM of the PP included 3D modeling results of the air inlet, the LPC with various air extractions to the third contour, and the jet nozzle taking into account the interaction between the basic stream and the third contour stream.The predicted performance of an air inlet have been used to estimate the changes in a total pressure restoration coefficient and an additional resistance coefficient along «a fluid contour» when air extraction is included in the third contour in several cruiser modes of flight.An integrated characteristic of the LPC has been received at various points and levels of air extraction to the third contour, and parameters of extracted air (depending on the point and amount of air extraction, and also on the fan operating mode have been calculated. When analyzing the obtained calculation results, the effect of pressure lines displacement to the right (towards the large reduced rates, growth of efficiency values, and also position displacement of its maximum value to the left (towards the descent reduced rates has been found.To estimate how air extraction of the third contour between the plates of an adjustable supersonic nozzle impacts on its aft deck resistance various parameters of

Active Shape Models (ASM) have proven to be an effective approach for image segmentation. In some applications, however, the linear model of gray level appearance around a contour that is used in ASM is not sufficient for accurate boundary localization. Furthermore, the statistical shape model may be too restricted if the training set is limited. This paper describes modifications to both the shape and the appearance model of the original ASM formulation. Shape model flexibility is increased, for tubular objects, by modeling the axis deformation independent of the cross-sectional deformation, and by adding supplementary cylindrical deformation modes. Furthermore, a novel appearance modeling scheme that effectively deals with a highly varying background is developed. In contrast with the conventional ASM approach, the new appearance model is trained on both boundary and non-boundary points, and the probability that a given point belongs to the boundary is estimated non-parametrically. The methods are evaluated on the complex task of segmenting thrombus in abdominal aortic aneurysms (AAA). Shape approximation errors were successfully reduced using the two shape model extensions. Segmentation using the new appearance model significantly outperformed the original ASM scheme; average volume errors are 5.1% and 45% respectively.

Programmable logic controllers (PLCs) were installed at several key ramps with the assistance of the City of Portland and used to capture additional data about ramp operations that are not otherwise logged. The data include include the activation and...

Programmable logic controllers (PLCs) were installed at several key ramps with the assistance of the City of Portland and used to capture additional data about ramp operations that are not otherwise logged. The data include the activation and deactiv...

Visual scenes can be readily decomposed into a variety of oriented components, the processing of which is vital for object segregation and recognition. In primate V1 and V2, most neurons have small spatio-temporal receptive fields responding selectively to oriented luminance contours (first order), while only a subgroup of neurons signal non-luminance defined contours (second order). So how is the orientation of second-order contours represented at the population level in macaque V1 and V2? Here we compared the population responses in macaque V1 and V2 to two types of second-order contour stimuli generated either by modulation of contrast or phase reversal with those to first-order contour stimuli. Using intrinsic signal optical imaging, we found that the orientation of second-order contour stimuli was represented invariantly in the orientation columns of both macaque V1 and V2. A physiologically constrained spatio-temporal energy model of V1 and V2 neuronal populations could reproduce all the recorded population responses. These findings suggest that, at the population level, the primate early visual system processes the orientation of second-order contours initially through a linear spatio-temporal filter mechanism. Our results of population responses to different second-order contour stimuli support the idea that the orientation maps in primate V1 and V2 can be described as a spatial-temporal energy map. PMID:25188576

We propose a novel associative memory model wherein the neural activity without an input (i.e., spontaneous activity) is modified by an input to generate a target response that is memorized for recall upon the same input. Suitable design of synaptic connections enables the model to memorize input/output (I/O) mappings equaling 70% of the total number of neurons, where the evoked activity distinguishes a target pattern from others. Spontaneous neural activity without an input shows chaotic dynamics but keeps some similarity with evoked activities, as reported in recent experimental studies.

Full Text Available Methodological approaches to the analysis of competitive activity of high qualification football teams are examined. Four tactical models of play of high qualification football teams: «A», «B», «C», «D», are identified on the basis of the developed method of competitive activity control, an integrated assessment of technical and tactical activity, and classification of interactions between players. Each of the models is characterized by the main components of competitive activity: positional attacks, high-speed attacks, pressing; passing the ball; modes of coordinative complexity of technical and tactical actions performance; specific indicators of the integral assessment of tactical activity.

Ten years of experience with analyses of students’ learning in a modelling course for first year university students, led us to see modelling as a didactical activity with the dual goal of developing students’ modelling competency and enhancing their conceptual learning of mathematical concepts i...... create and help overcome hidden cognitive conflicts in students’ understanding; that reflections within modelling can play an important role for the students’ learning of mathematics. These findings are illustrated with a modelling project concerning the world population....

It is widely accepted that illusory contours have been first displayed and discussed by Schumann (1900, Zeitschrift für Psychologie und Physiologie der Sinnesorgane 23 1-32). Here we show that, before him, Jastrow (1899, Popular Science Monthly 54 299-312) produced illusory contours consisting of a shadow word. A brief history of shadow writing in psychological literature from Jastrow to Brunswik is presented, in which the contributions of Pillsbury, Warren, Koffka, and Benussi are examined.

Full Text Available Illusory contours are specific class of visual stimuli that represent stimuli configurations perceived as integral irrespective of the fact that they are given in fragmented uncompleted wholes. Due to their specific features, illusory contours gained much attention in last decade representing prototype of stimuli used in investigations focused on binding problem. On the other side, investigations of illusory contours are related to problem of the level of their visual processing. Neurophysiologic studies show that processing of illusory contours proceed relatively early, on the V2 level, on the other hand most of experimental studies claim that illusory contours are perceived with engagement of visual attention, binding their elements to whole percept. This research is focused on two experiments in which visual search of illusory contours are based on shape and orientation. The main experimental procedure evolved the task proposed by Bravo and Nakayama where instead of detection, subjects were performing identification of one among two possible targets. In the first experiment subjects detected the presence of illusory square or illusory triangle, while in the second experiment subject were detecting two different orientations of illusory triangle. The results are interpreted in terms of visual search and feature integration theory. Beside the type of visual search task, search type proved to be dependent of specific features of illusory shapes which further complicate theoretical interpretation of the level of their perception.

The majority of work on the perception of transparency has focused on static images with luminance-defined contour junctions, but recent work has shown that dynamic image sequences with dynamic image deformations also provide information about transparency. The present study demonstrates that when part of a static image is dynamically deformed, contour junctions at which deforming and nondeforming contours are connected facilitate the deformation-based perception of a transparent layer. We found that the impression of a transparent layer was stronger when a dynamically deforming area was adjacent to static nondeforming areas than when presented alone. When contour junctions were not formed at the dynamic-static boundaries, however, the impression of a transparent layer was not facilitated by the presence of static surrounding areas. The effect of the deformation-defined junctions was attenuated when the spatial pattern of luminance contrast at the junctions was inconsistent with the perceived transparency related to luminance contrast, while the effect did not change when the spatial luminance pattern was consistent with it. In addition, the results showed that contour completions across the junctions were required for the perception of a transparent layer. These results indicate that deformation-defined junctions that involve contour completion between deforming and nondeforming regions enhance the perception of a transparent layer, and that the deformation-based perceptual transparency can be promoted by the simultaneous presence of appropriately configured luminance and contrast-other features that can also by themselves produce the sensation of perceiving transparency.

The authors show how complex paths can be consistently introduced into sums for Feynman histories by using the notion of functional contour integration. For a kappa-dimensional system specified by a potential with suitable analyticity properties, each coordinate axis is replaced by a copy of the complex plane, and at each instant of time a contour is chosen in each plane. This map from the time axis into the set of complex contours defines a functional contour. The family of contours labelled by time generates a (kappa+1)-dimensional submanifold of the (2kappa+1)-dimensional space defined by the cartesian product of the time axis and the coordinate planes. The complex Feynman paths lie on this submanifold. An application of this idea to systems described by absorptive potentials yields a simple derivation of the correct WKB result in terms of a complex path that extremalises the action. The method can also be applied to spherically symmetric potentials by using a partial wave expansion and restricting the contours appropriately. (author)

This paper aims to explain results of respirometry experiments using Activated Sludge Model No. 1. In cases of insufficient fit of ASM No. 1, further modifications to the model were carried out and the so-called "Enzymatic model" was developed. The best-fit method was used to determine the effect of

Indonesia imports fuel (fuel oil) in large quantities. Indonesia has reserves of methane gas in the form of natural gas in large numbers but has obstacles in the process of storage. To produce a storage tank to a safe condition then proclaimed to use ANG (Adsorbed Natural Gas) technology. Manufacture of activated PET based activated carbon for storage of natural gas where technology has been widely studied, but still has some shortcomings. Therefore to predict the performance of ANG technology, modeling of ANG tank with Fluent CFD program is done so the condition inside the ANG tank can be known and can be used to increased the performance of ANG technology. Therefore, in this experiment natural gas storage test is done at the ANG tank model using Fluent CFD program. This experiment is begin with preparation tools and material by characterize the natural gas and activated carbon followed by create the mesh and model of ANG tank. The next process is state the characteristic of activated carbon and fluid in this experiment. The last process is run the simulation using the condition that already been stated which is at 27°C and 35 bar during 15 minutes. The result is at adsorption contour we can see that adsorption is higher at the top of the tank because the input of the adsorbent is at the top of the ANG tank so the adsorbate distribution is uneven that cause the adsorbate concentration at the top of the ANG tank is higher than the bottom tank.

The activation and transport of corrosion products around a PWR circuit is a major concern to PWR plant operators as these may give rise to high personnel doses. The understanding of what controls dose rates on ex-core surfaces and shutdown releases has improved over the years but still several questions remain unanswered. For example the relative importance of particle and soluble deposition in the core to activity levels in the plant is not clear. Wide plant to plant and cycle to cycle variations are noted with no apparent explanations why such variations are observed. Over the past few years this group have been developing models to simulate corrosion product transport around a PWR circuit. These models form the basis for the latest version of the BOA code and simulate the movement of Fe and Ni around the primary circuit. Part of this development is to include the activation and subsequent transport of radioactive species around the circuit and this paper describes some initial modelling work in this area. A simple model of activation, release and deposition is described and then applied to explain the plant behaviour at Sizewell B and Vandellos II. This model accounts for activation in the core, soluble and particulate activity movement around the circuit and for activity capture ex-core on both the inner and outer oxides. The model gives a reasonable comparison with plant observations and highlights what controls activity transport in these plants and importantly what factors can be ignored. (authors)

Full Text Available Visual contours often result from the integration or interpolation of fragmented edges.The strength of the completion increases when the edges share the same contrast polarity (CP. Here we demonstrate that the appearance in the perceptual field of this integrated unit, or contour of invariant CP, is concomitant with a vivid brightness alteration of the surfaces at its opposite sides. To observe this effect requires some stratagems because the formation in the visual field of a contour of invariant CP normally engenders the formation of a second contour and then the rise of two streams of induction signals that interfere in different ways. Particular configurations have been introduced that allow us to observe the induction effects of one contour taken in isolation. I documented these effects by phenomenological observations and psychophysical measurement of the brightness alteration in relation to luminance contrast. When the edges of the same CP complete to form a contour, the background of homogeneous luminance appears to dim at one side and to brighten at the opposite side (in accord with the CP. The strength of the phenomenon is proportional to the local luminance contrast. This effect weakens or nulls when the contour of the invariant CP separates surfaces filled with different grey shades.These conflicting results stimulate a deeper exploration of the induction phenomena and their role in the computation of brightness contrast. An alternative perspective is offered to account for some brightness illusions and their relation to the phenomenal transparency. The main assumption asserts that, when in the same region induction signals of opposite CP overlap, the filling-in are blocked unless the image is stratified into different layers, one for each signal of the same polarity. Phenomenological observations document this solution by the visual system

The Wright Brothers marked the beginning of powered flight in 1903 using an active twist mechanism as their means of controlling roll. As time passed due to advances in other technologies that transformed aviation the active twist mechanism was no longer used. With the recent advances in material science and manufacturability, the possibility of the practical use of active twist technologies has emerged. In this dissertation, the advantages and disadvantages of active twist techniques are investigated through the development of an aeroelastic modeling method intended for informing the designs of such technologies and wind tunnel testing to confirm the capabilities of the active twist technologies and validate the model. Control principles for the enabling structural technologies are also proposed while the potential gains of dynamic, active twist are analyzed.

This paper demonstrates that (near) real-time object tracking can be accomplished by the deformable template model; the Active Appearance Model (AAM) using only low-cost consumer electronics such as a PC and a web-camera. Successful object tracking of perspective, rotational and translational...

The results of the mathematical modeling of vibroseismic monitoring of changes in the elastic characteristics in the interior Earth's crust zone are presented. The model of the 'Earth's crust-mantle' system with point vibrational source on the free surface is considered. The estimates of sensitivity of active monitoring method with harmonic vibrational signals is determined. (author)

We propose the LEMAIO multi-layer framework, which makes use of hierarchical abstraction to learn models for activities involving multiple interacting objects from time sequences of data concerning the individual objects. Experiments in the sea navigation domain yielded learned models that were t...

Vision is the key component of Artificial Intelligence and Automated Robotics. Sensors or Cameras are the sight organs for a robot. Only through this, they are able to locate themselves or identify the shape of a regular or an irregular object. This paper presents the method of Identification of an object based on color and contour recognition using a camera through digital image processing techniques for robotic applications. In order to identify the contour, shape matching technique is used, which takes the input data from the database provided, and uses it to identify the contour by checking for shape match. The shape match is based on the idea of iterating through each contour of the threshold image. The color is identified on HSV Scale, by approximating the desired range of values from the database. HSV data along with iteration is used for identifying a quadrilateral, which is our required contour. This algorithm could also be used in a non-deterministic plane, which only uses HSV values exclusively.

As data sets grow to exascale, automated data analysis and visualisation are increasingly important, to intermediate human understanding and to reduce demands on disk storage via in situ analysis. Trends in architecture of high performance computing systems necessitate analysis algorithms to make effective use of combinations of massively multicore and distributed systems. One of the principal analytic tools is the contour tree, which analyses relationships between contours to identify features of more than local importance. Unfortunately, the predominant algorithms for computing the contour tree are explicitly serial, and founded on serial metaphors, which has limited the scalability of this form of analysis. While there is some work on distributed contour tree computation, and separately on hybrid GPU-CPU computation, there is no efficient algorithm with strong formal guarantees on performance allied with fast practical performance. Here in this paper, we report the first shared SMP algorithm for fully parallel contour tree computation, withfor-mal guarantees of O(lgnlgt) parallel steps and O(n lgn) work, and implementations with up to 10x parallel speed up in OpenMP and up to 50x speed up in NVIDIA Thrust.

We are developing a computerized system for bladder segmentation on CT urography (CTU), as a critical component for computer-aided detection of bladder cancer. The presence of regions filled with intravenous contrast and without contrast presents a challenge for bladder segmentation. Previously, we proposed a conjoint level set analysis and segmentation system (CLASS). In case the bladder is partially filled with contrast, CLASS segments the non-contrast (NC) region and the contrast-filled (C) region separately and automatically conjoins the NC and C region contours; however, inaccuracies in the NC and C region contours may cause the conjoint contour to exclude portions of the bladder. To alleviate this problem, we implemented a local contour refinement (LCR) method that exploits model-guided refinement (MGR) and energy-driven wavefront propagation (EDWP). MGR propagates the C region contours if the level set propagation in the C region stops prematurely due to substantial non-uniformity of the contrast. EDWP with regularized energies further propagates the conjoint contours to the correct bladder boundary. EDWP uses changes in energies, smoothness criteria of the contour, and previous slice contour to determine when to stop the propagation, following decision rules derived from training. A data set of 173 cases was collected for this study: 81 cases in the training set (42 lesions, 21 wall thickenings, 18 normal bladders) and 92 cases in the test set (43 lesions, 36 wall thickenings, 13 normal bladders). For all cases, 3D hand segmented contours were obtained as reference standard and used for the evaluation of the computerized segmentation accuracy. For CLASS with LCR, the average volume intersection ratio, average volume error, absolute average volume error, average minimum distance and Jaccard index were 84.2 ± 11.4%, 8.2 ± 17.4%, 13.0 ± 14.1%, 3.5 ± 1.9 mm, 78.8 ± 11.6%, respectively, for the training set and 78.0 ± 14.7%, 16.4 ± 16.9%, 18.2 ± 15

Full Text Available In order to analyze the influence of technical parameters on work roll axial force of four-high continuous variable crown (CVC mill, the deformation analyzing model with top roll system and strip was established based on influence function method. Then a CVC work roll curve designing scheme was proposed and it was carried out on some cold rolling mill considering the requirement of comprehensive work roll axial force minimization. The status of comprehensive work roll axial force is improved considering the rolling schedule that is beneficial to the roller bearing. Corresponding to the newly designed work roll contour, the backup roll end chamfer was designed considering comprehensive performance of interroll stress concentration, comprehensive work roll axial force, and strip shape control ability. The distribution of roll wear with newly designed backup roll contour is more even according to the field application data. The newly established roll configuration scheme is beneficial to four-high CVC mill.

The impacts of strategically located contour prairie strips on sediment and nutrient runoff export from watersheds maintained under an annual row crop production system have been studied at a long-term research site in central Iowa. Data from 2007 to 2011 indicate that the contour prairie strips utilized within row crop-dominated landscapes have greater than proportionate and positive effects on the functioning of biophysical systems. Crop producers and land management agencies require comprehensive information about the Best Management Practices with regard to performance efficacy, operational/management parameters, and the full range of financial parameters. Here, a farm-level financial model assesses the establishment, management, and opportunity costs of contour prairie strips within cropped fields. Annualized, depending on variable opportunity costs the 15-year present value cost of utilizing contour prairie strips ranges from $590 to $865 ha(-1) year(-1) ($240-$350 ac(-1) year(-1)). Expressed in the context of "treatment area" (e.g., in this study 1 ha of prairie treats 10 ha of crops), the costs of contour prairie strips can also be viewed as $59 to about $87 per treated hectare ($24-$35 ac(-1)). If prairie strips were under a 15-year CRP contract, total per acre cost to farmers would be reduced by over 85 %. Based on sediment, phosphorus, and nitrogen export data from the related field studies and across low, medium, and high land rent scenarios, a megagram (Mg) of soil retained within the watershed costs between $7.79 and $11.46 mg(-1), phosphorus retained costs between $6.97 and $10.25 kg(-1), and nitrogen retained costs between $1.59 and $2.34 kg(-1). Based on overall project results, contour prairie strips may well become one of the key conservation practices used to sustain US Corn Belt agriculture in the decades to come.

This review discusses a set of simple models for cool-star activity with which we compute (1) photospheric field patterns on stars of different activity levels, (2) the associated outer-atmospheric field configurations, and (3) the soft X-ray emission that is expected to result from the ensemble of loop atmospheres in the coronae of these stars. The model is based on empirically-determined properties of solar activity. It allows us to extrapolate to stars of significantly higher and lower activity than seen on the present-day Sun through its cycle. With it, we can, for example, gain insight into stellar field patterns (including a possible formation mechanism for polar starspots), as well as in the properties of coronal heating (helpful in the identification of the quiescent coronal heating mechanism). Lacking comprehensive theoretical understanding, the model's reliance on empirical solar data means that the multitude of processes involved are approximated to be independent of rotation rate, activity level, and fundamental stellar parameters, or -- where unavoidably necessary -- assumed to simply scale with activity. An evaluation of the most important processes involved guides a discussion of the limits of the model, of the limitations in our knowledge, and of future needs. "I propose to adopt such rules as will ensure the testability of scientific statements; which is to say, their falsifiability." Karl Popper (1902-1994)

The magnitudes of chromatic and achromatic edge contrast are statistically independent and thus provide independent information, which can be used for object-contour perception. However, it is unclear if and how much object-contour perception benefits from chromatic edge contrast. To address this question, we investigated how well human-marked object contours can be predicted from achromatic and chromatic edge contrast. We used four data sets of human-marked object contours with a total of 824 images. We converted the images to the Derrington-Krauskopf-Lennie color space to separate chromatic from achromatic information in a physiologically meaningful way. Edges were detected in the three dimensions of the color space (one achromatic and two chromatic) and compared to human-marked object contours using receiver operating-characteristic (ROC) analysis for a threshold-independent evaluation. Performance was quantified by the difference of the area under the ROC curves (ΔAUC). Results were consistent across different data sets and edge-detection methods. If chromatic edges were used in addition to achromatic edges, predictions were better for 83% of the images, with a prediction advantage of 3.5% ΔAUC, averaged across all data sets and edge detectors. For some images the prediction advantage was considerably higher, up to 52% ΔAUC. Interestingly, if achromatic edges were used in addition to chromatic edges, the average prediction advantage was smaller (2.4% ΔAUC). We interpret our results such that chromatic information is important for object-contour perception.

It has long been known that colored images may elicit afterimages in complementary colors. We have already shown (Van Lier, Vergeer, & Anstis, 2009) that one and the same adapting image may result in different afterimage colors, depending on the test contours presented after the colored image. The color of the afterimage depends on two adapting colors, those both inside and outside the test. Here, we further explore this phenomenon and show that the color-contour interactions shown for afterimage colors also occur for "real" colors. We argue that similar mechanisms apply for both types of stimulation.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

In this work we present a technique to extract the heart contours from noisy echocardiograph images. Our technique is based on improving the image before applying contours detection to reduce heavy noise and get better image quality. To perform that, we combine many pre-processing techniques (filtering, morphological operations, and contrast adjustment) to avoid unclear edges and enhance low contrast of echocardiograph images, after implementing these techniques we can get legible detection for heart boundaries and valves movement by traditional edge detection methods.

Bariatric surgery is a way to achieve lasting weight loss in the obese. Body contouring surgery seeks to alleviate some of the discomfort caused by the excessive loose skin following massive weight loss. Higher complication rates are described in this type of surgery when done post......-bariatric. The purpose of this article is to compare complication rates of body contouring surgery when performed on patients with weight loss due to bariatric surgery compared to patients who lost weight due to dietary changes and/or exercise....

Full Text Available The article discusses the principles and mechanisms of formation of the contour of the real safety of flights and contour of the documented safety, allowing us to obtain information to control fligh safety. The proposed approach can be used in the algorithms of active on-board flight safety management system for the implementation of information support to the crew in flight and automatic control of flight safety.

Axelrod's model was proposed to study interactions between agents and the formation of cultural domains. It presents a transition from a monocultural to a multicultural steady state which has been studied in the literature by evaluation of the relative size of the largest cluster. In this article, we propose new measurements based on the concept of activity per agent to study the Axelrod's model on the square lattice. We show that the variance of system activity can be used to indicate the critical points of the transition. Furthermore the frequency distribution of the system activity is able to show a coexistence of phases typical of a first order phase transition. Finally, we verify a power law dependence between cluster activity and cluster size for multicultural steady state configurations at the critical point.

Full Text Available In this article we propose a novel method to automatically set the initial contour that is used by the Activecontours algorithm.The proposed method exploits the accumulative intensity profiles to locate the points on the arterial wall. The intensity profiles of sections that intersect the artery show distinguishable characterstics that make it possible to recognize them from the profiles of sections that do not intersect the artery walls. The proposed method is applied on ultrasound images of the transverse section of the common carotid artery, but it can be extended to be used on the images of the longitudinal section. The intensity profiles are classified using Support vector machine algorithm, and the results of different kernels are compared. The extracted features used for the classification are basically statistical features of the intensity profiles. The echogenicity of the arterial lumen, and gives the profiles that intersect the artery a special shape that helps recognizing these profiles from other general profiles.The outlining of the arterial walls may seem a classic task in image processing. However, most of the methods used to outline the artery start from a manual, or semi-automatic, initial contour.The proposed method is highly appreciated in automating the entire process of automatic artery detection and segmentation.

Full Text Available This paper describes active suspension with active roll for four-wheel vehicle (bus by means of an in-series pump actuator with doubled hydropneumatic springs. It also gives full control law with no sky-craping. Lateral stiffness and solid axle geometry in the mechanical model are not neglected. Responses to lateral input as well as responses to statistical unevennesses show considerable improvement of passengers comfort and safety when cornering.

Understanding the uncertainty in wind plant performance is crucial to their cost-effective design and operation. However, conventional approaches to uncertainty quantification (UQ), such as Monte Carlo techniques or surrogate modeling, are often computationally intractable for utility-scale wind plants because of poor congergence rates or the curse of dimensionality. In this paper we demonstrate that wind plant power uncertainty can be well represented with a low-dimensional active subspace, thereby achieving a significant reduction in the dimension of the surrogate modeling problem. We apply the active sub-spaces technique to UQ of plant power output with respect to uncertainty in turbine axial induction factors, and find a single active subspace direction dominates the sensitivity in power output. When this single active subspace direction is used to construct a quadratic surrogate model, the number of model unknowns can be reduced by up to 3 orders of magnitude without compromising performance on unseen test data. We conclude that the dimension reduction achieved with active subspaces makes surrogate-based UQ approaches tractable for utility-scale wind plants.

been explored in this thesis by considering them as epidemic-like processes. A mathematical model has been developed based on differential equations, which studies the dynamics of the issues from the very beginning until the issues cease. This study extends classical models of the spread of epidemics...... to describe the phenomenon of contagious public outrage, which eventually leads to the spread of violence following a disclosure of some unpopular political decisions and/or activity. The results shed a new light on terror activity and provide some hint on how to curb the spreading of violence within...

Background Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. Methodology First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. Conclusions We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery. PMID:19547712

Full Text Available BACKGROUND: Dynamical systems like neural networks based on lateral inhibition have a large field of applications in image processing, robotics and morphogenesis modeling. In this paper, we will propose some examples of dynamical flows used in image contrasting and contouring. METHODOLOGY: First we present the physiological basis of the retina function by showing the role of the lateral inhibition in the optical illusions and pathologic processes generation. Then, based on these biological considerations about the real vision mechanisms, we study an enhancement method for contrasting medical images, using either a discrete neural network approach, or its continuous version, i.e. a non-isotropic diffusion reaction partial differential system. Following this, we introduce other continuous operators based on similar biomimetic approaches: a chemotactic contrasting method, a viability contouring algorithm and an attentional focus operator. Then, we introduce the new notion of mixed potential Hamiltonian flows; we compare it with the watershed method and we use it for contouring. CONCLUSIONS: We conclude by showing the utility of these biomimetic methods with some examples of application in medical imaging and computed assisted surgery.

Full Text Available Tuberculosis (TB is one of the most common infectious diseases worldwide. It is estimated that one-third of the world’s population is infected with TB. Most have the latent stage of the disease that can later transition to active TB disease. TB is spread by aerosol droplets containing Mycobacterium tuberculosis (Mtb. Mtb bacteria enter through the respiratory system and are attacked by the immune system in the lungs. The bacteria are clustered and contained by macrophages into cellular aggregates called granulomas. These granulomas can hold the bacteria dormant for long periods of time in latent TB. The bacteria can be perturbed from latency to active TB disease in a process called granuloma activation when the granulomas are compromised by other immune response events in a host, such as HIV, cancer, or aging. Dysregulation of matrix metalloproteinase 1 (MMP-1 has been recently implicated in granuloma activation through experimental studies, but the mechanism is not well understood. Animal and human studies currently cannot probe the dynamics of activation, so a computational model is developed to fill this gap. This dynamic mathematical model focuses specifically on the latent to active transition after the initial immune response has successfully formed a granuloma. Bacterial leakage from latent granulomas is successfully simulated in response to the MMP-1 dynamics under several scenarios for granuloma activation.

In this paper, a new technique for offline writer identification is presented, using connected-component contours (COCOCOs or CO(3)s) in uppercase handwritten samples. In our model, the writer is considered to be characterized by a stochastic pattern generator, producing a family of connected

We have developed a new method of accurately profiling a mask shape by utilizing a Mask CD-SEM. The method is intended to realize high accuracy, stability and reproducibility of the Mask CD-SEM adopting an edge detection algorithm as the key technology used in CD-SEM for high accuracy CD measurement. In comparison with a conventional image processing method for contour profiling, it is possible to create the profiles with much higher accuracy which is comparable with CD-SEM for semiconductor device CD measurement. In this report, we will introduce the algorithm in general, the experimental results and the application in practice. As shrinkage of design rule for semiconductor device has further advanced, an aggressive OPC (Optical Proximity Correction) is indispensable in RET (Resolution Enhancement Technology). From the view point of DFM (Design for Manufacturability), a dramatic increase of data processing cost for advanced MDP (Mask Data Preparation) for instance and surge of mask making cost have become a big concern to the device manufacturers. In a sense, it is a trade-off between the high accuracy RET and the mask production cost, while it gives a significant impact on the semiconductor market centered around the mask business. To cope with the problem, we propose the best method for a DFM solution in which two dimensional data are extracted for an error free practical simulation by precise reproduction of a real mask shape in addition to the mask data simulation. The flow centering around the design data is fully automated and provides an environment where optimization and verification for fully automated model calibration with much less error is available. It also allows complete consolidation of input and output functions with an EDA system by constructing a design data oriented system structure. This method therefore is regarded as a strategic DFM approach in the semiconductor metrology.

The automatic generation of planning targets and auxiliary contours have achieved in Eclipse TPS 11.0. The scripting language autohotkey was used to develop a software for automatically generated contours in Eclipse TPS. This software is named Contour Auto Margin (CAM), which is composed of operational functions of contours, script generated visualization and script file operations. RESULTS Ten cases in different cancers have separately selected, in Eclipse TPS 11.0 scripts generated by the software could not only automatically generate contours but also do contour post-processing. For different cancers, there was no difference between automatically generated contours and manually created contours. The CAM is a user-friendly and powerful software, and can automatically generated contours fast in Eclipse TPS 11.0. With the help of CAM, it greatly save plan preparation time and improve working efficiency of radiation therapy physicists.

Kittens do not learn to use visual information to guide their behaviour if they are deprived of the optic flow that accompanies their own movements. We show that the optic flow that is required for developing visually guided behaviour is derived from changes in contour orientations, rather than from

It has long been known that colored images may elicit afterimages in complementary colors. We have already shown (Van Lier, Vergeer, & Anstis, 2009) that one and the same adapting image may result in different afterimage colors, depending on the test contours presented after the colored image. The

We propose a biologically motivated computational step, called non-classical receptive field (non-CRF) inhibition, to improve the performance of contour detectors. Non-CRF inhibition is exhibited by 80% of the orientation selective neurons in the primary visual cortex of macaque monkeys and has been

We propose a biologically motivated computational step, called nonclassical receptive field (non-CRF) inhibition, more generally surround inhibition or suppression, to improve contour detection in machine vision. Non-CRF inhibition is exhibited by 80% of the orientation-selective neurons in the

In article is brought analysis of diverse gases diffusion coefficients computation methods, dissolved in liquid. On the basis of this analysis and treatment of being equalizations for concrete gases and certain parameters offers universal diffusion coefficients determination dependence for diverse gases in wide range of parameters, circulation contours typical for work NPP

The added functionality such as contour tracking and corner detection which logic programming lends to standard image operators is described. An environment for implementing low-level imaging operations with Prolog predicates is considered. Within this environment, higher-level image predicates (...

Techniques and concepts for treatment of the aging neck have been evolving since the late 1960s and rely on two-dimensional anterior approximation with lateral imbrication of the platysma with or without submental fat reduction, However, the medial approximation can sometimes give a "boxy" appearance to the anterior neck, especially if anterior shifting of the platysma recurs after platysmaplasty with laxity redeveloping in this midline location. The "purse-string" platysmaplasty (PSP) is a new concept in neck contouring that facilitates an enhanced definition for the cervicomandibular transition to better simulate the well-defined contour of this transition that is present in youth. It aids in the contouring of difficult poorly defined necks and in male patients. The PSP adds a "third dimension" to neck recontouring by invaginating the platysma with a plication suture and pexing the platysma, without incising it, to deeper neck fascia with a technique that adds support and definition to the neck contour. The PSP can be performed in patients undergoing a full rhytidectomy as well as in individuals having isolated neck rejuvenation. The PSP is especially helpful in rejuvenating the male lower face and neck because of the relatively heavier deeper structures of the male neck and the need to enhance definition along the jawline.

In this paper a contour detection method is described and evaluated on the evaluation data sets of the Cardiac MR Left Ventricle Segmentation Challenge as part of MICCAI 2009s 3D Segmentation Challenge for Clinical Applications. The proposed method, using 2D AAM and 3D ASM, performs a fully

Full Text Available A vibrotactile array is a promising human computer interface which could display graphical information to users in a tactile form. This paper presents the design and testing of an image contour display system with a vibrotactile array. The tactile image display system is attached to the back of the user. It converts visual graphics into 2D tactile images and allows subjects to feel the contours of objects through vibration stimulus. The system consists of a USB camera, 48 (6×8 vibrating motors and an embedded control system. The image is captured by the camera and the 2D contour is extracted and transformed into vibrotactile stimuli using a temporal-spatial dynamic coding method. Preliminary experiments were carried out and the optimal parameters of the vibrating time and duration were explored. To evaluate the feasibility and robustness of this vibration mode, letters were also tactilely displayed and the recognition rate about the alphabet letter display was investigated. It was shown that under the condition of no pre-training for the subjects, the recognition rate was 82%. Such a recognition rate is higher than that of the scanning mode (47.5% and the improved handwriting mode (76.8%. The results indicated that the proposed method was efficient in conveying the contour information to the visually impaired by means of vibrations.

The consumption of nutrients by mussel beds can be monitored by measuring the net nutrient flux across a circumscribing vertical surface. Measuring this nutrient flux not only requires resolving the spatial (and temporal) distribution of nutrients at the bounding contour, but also an ability to

The paper presents a mathematical model of total mercury removed from the flue gas at coal-fired plants equipped with powdered activated carbon (PAC) injection for Mercury control. The developed algorithms account for mercury removal by both existing equipment and an added PAC in...

An overview of the activities undertaken by IAEA inspectors at the model research reactor and research laboratories is given. The basic philosophy behind nuclear material stratification and the concepts of Material Balance Areas and Key Measurement Points are explained. Diversion routes and plausible diversion scenarios are analysed. 8 refs., 6 figs., 3 tabs., poster presentations included

Full Text Available To develop model-based control strategies for Functional Electrical Stimulation (FES in order to support weak voluntary muscle contractions, a hybrid model for describing joint motions induced by concurrent voluntary-and FES induced muscle activation is proposed. It is based on a Hammerstein model – as commonly used in feedback controlled FES – and exemplarily applied to describe the shoulder abduction joint angle. Main component of a Hammerstein muscle model is usually a static input nonlinearity depending on the stimulation intensity. To additionally incorporate voluntary contributions, we extended the static non-linearity by a second input describing the intensity of the voluntary contribution that is estimated by electromyography (EMG measurements – even during active FES. An Artificial Neural Network (ANN is used to describe the static input non-linearity. The output of the ANN drives a second-order linear dynamical system that describes the combined muscle activation and joint angle dynamics. The tunable parameters are adapted to the individual subject by a system identification approach using previously recorded I/O-data. The model has been validated in two healthy subjects yielding RMS values for the joint angle error of 3.56° and 3.44°, respectively.

Present work describes a mathematical model that quantifies the time dependent amount of {sup 222}Rn and {sup 220}Rn altogether and their activities within an ionization chamber as, for example, AlphaGUARD, which is used to measure activity concentration of Rn in soil gas. The differential equations take into account tree main processes, namely: the injection of Rn into the cavity of detector by the air pump including the effect of the traveling time Rn takes to reach the chamber; Rn release by the air exiting the chamber; and radioactive decay of Rn within the chamber. Developed code quantifies the activity of {sup 222}Rn and {sup 220}Rn isotopes separately. Following the standard methodology to measure Rn activity in soil gas, the air pump usually is turned off over a period of time in order to avoid the influx of Rn into the chamber. Since {sup 220}Rn has a short half-life time, approximately 56s, the model shows that after 7 minutes the activity concentration of this isotope is null. Consequently, the measured activity refers to {sup 222}Rn, only. Furthermore, the model also addresses the activity of {sup 220}Rn and {sup 222}Rn progeny, which being metals represent potential risk of ionization chamber contamination that could increase the background of further measurements. Some preliminary comparison of experimental data and theoretical calculations is presented. Obtained transient and steady-state solutions could be used for planning of Rn in soil gas measurements as well as for accuracy assessment of obtained results together with efficiency evaluation of chosen measurements procedure. (author)

In real-world conditions, contours are most often blurred in digital images because of acquisition conditions such as movement, light transmission environment, and defocus. Among image segmentation methods, Hough transform requires a computational load which increases with the number of noise pixels, level set methods also require a high computational load, and some other methods assume that the contours are one-pixel wide. For the first time, we retrieve the characteristics of multiple possibly concentric blurred circles. We face correlated noise environment, to get closer to real-world conditions. For this, we model a blurred circle by a few parameters--center coordinates, radius, and spread--which characterize its mean position and gray level variations. We derive the signal model which results from signal generation on circular antenna. Linear antennas provide the center coordinates. To retrieve the circle radii, we adapt the second-order statistics TLS-ESPRIT method for non-correlated noise environment, and propose a novel version of TLS-ESPRIT based on higher-order statistics for correlated noise environment. Then, we derive a least-squares criterion and propose an alternating least-squares algorithm to retrieve simultaneously all spread values of concentric circles. Experiments performed on hand-made and real-world images show that the proposed methods outperform the Hough transform and a level set method dedicated to blurred contours in terms of computational load. Moreover, the proposed model and optimization method provide the information of the contour grey level variations.

ENGLISH ABSTRACT: This paper presents a new procedure for analysing and managing activity sequences in projects. The new procedure determines critical activities, critical path, start times, free floats, crash limits, and other useful information without the use of the network model. Even though network models have been successfully used in project management so far, there are weaknesses associated with the use. A network is not easy to generate, and dummies that are usually associated with it make the network diagram complex – and dummy activities have no meaning in the original project management problem. The network model for projects can be avoided while still obtaining all the useful information that is required for project management. What are required are the activities, their accurate durations, and their predecessors.

In SAR image interpretation, aircrafts are the important targets arousing much attention. However, it is far from easy to segment an aircraft from the background completely and precisely in SAR images. Because of the complex structure, different kinds of electromagnetic scattering take place on the aircraft surfaces. As a result, aircraft targets usually appear to be inhomogeneous and disconnected. It is a good idea to extract an aircraft target by the active shape model (ASM), since combination of the geometric information controls variations of the shape during the contour evolution. However, linear dimensionality reduction, used in classic ACM, makes the model rigid. It brings much trouble to segment different types of aircrafts. Aiming at this problem, an improved ACM based on ISOMAP is proposed in this paper. ISOMAP algorithm is used to extract the shape information of the training set and make the model flexible enough to deal with different aircrafts. The experiments based on real SAR data shows that the proposed method achieves obvious improvement in accuracy.

Full Text Available In this paper we present a novel unsupervised approach to detecting and segmenting objects as well as their constituent symmetric parts in an image. Traditional unsupervised image segmentation is limited by two obvious deficiencies: the object detection accuracy degrades with the misaligned boundaries between the segmented regions and the target, and pre-learned models are required to group regions into meaningful objects. To tackle these difficulties, the proposed approach aims at incorporating the pair-wise detection of symmetric patches to achieve the goal of segmenting images into symmetric parts. The skeletons of these symmetric parts then provide estimates of the bounding boxes to locate the target objects. Finally, for each detected object, the graphcut-based segmentation algorithm is applied to find its contour. The proposed approach has significant advantages: no a priori object models are used, and multiple objects are detected. To verify the effectiveness of the approach based on the cues that a face part contains an oval shape and skin colors, human objects are extracted from among the detected objects. The detected human objects and their parts are finally tracked across video frames to capture the object part movements for learning the human activitymodels from video clips. Experimental results show that the proposed method gives good performance on publicly available datasets.

Background: Radiation therapy treatment planning has advanced over the past 2 decades, with increased emphasis on 3-dimensional imaging for target and organ-at-risk (OAR) delineation. Recent studies suggest a need for improved resident instruction in this area. We developed and evaluated an intensive national educational course (“boot camp”) designed to provide dedicated instruction in site-specific anatomy, radiology, and contouring using a multidisciplinary (MDT) approach. Methods: The anatomy and radiology contouring (ARC) boot camp was modeled after prior single-institution pilot studies and a needs-assessment survey. The boot camp incorporated joint lectures from radiation oncologists, anatomists, radiologists, and surgeons, with hands-on contouring instruction and small group interactive seminars using cadaveric prosections and correlative axial radiographs. Outcomes were evaluated using pretesting and posttesting, including anatomy/radiology multiple-choice questions (MCQ), timed contouring sessions (evaluated relative to a gold standard using Dice similarity metrics), and qualitative questions on satisfaction and perceived effectiveness. Analyses of pretest versus posttest scores were performed using nonparametric paired testing. Results: Twenty-nine radiation oncology residents from 10 Canadian universities participated. As part of their current training, 29%, 75%, and 21% receive anatomy, radiology, and contouring instruction, respectively. On posttest scores, the MCQ knowledge scores improved significantly (pretest mean 60% vs posttest mean 80%, Pcontoured structures, there was a 0.20 median improvement in students' average Dice score (Pcontour OARs and interpret radiographs in all anatomic sites, 92% of students found the MDT format effective for their learning, and 93% found the boot camp

Background: Radiation therapy treatment planning has advanced over the past 2 decades, with increased emphasis on 3-dimensional imaging for target and organ-at-risk (OAR) delineation. Recent studies suggest a need for improved resident instruction in this area. We developed and evaluated an intensive national educational course (“boot camp”) designed to provide dedicated instruction in site-specific anatomy, radiology, and contouring using a multidisciplinary (MDT) approach. Methods: The anatomy and radiology contouring (ARC) boot camp was modeled after prior single-institution pilot studies and a needs-assessment survey. The boot camp incorporated joint lectures from radiation oncologists, anatomists, radiologists, and surgeons, with hands-on contouring instruction and small group interactive seminars using cadaveric prosections and correlative axial radiographs. Outcomes were evaluated using pretesting and posttesting, including anatomy/radiology multiple-choice questions (MCQ), timed contouring sessions (evaluated relative to a gold standard using Dice similarity metrics), and qualitative questions on satisfaction and perceived effectiveness. Analyses of pretest versus posttest scores were performed using nonparametric paired testing. Results: Twenty-nine radiation oncology residents from 10 Canadian universities participated. As part of their current training, 29%, 75%, and 21% receive anatomy, radiology, and contouring instruction, respectively. On posttest scores, the MCQ knowledge scores improved significantly (pretest mean 60% vs posttest mean 80%, Pcontoured structures, there was a 0.20 median improvement in students' average Dice score (Pcontour OARs and interpret radiographs in all anatomic sites, 92% of students found the MDT format effective for their learning, and 93% found the boot camp

Purpose: To develop a set of atlases for automatic contouring of cardiac structures to determine heart radiation dose and the associated toxicity. Methods: Six thoracic cancer patients with both contrast and non-contrast CT images were acquired for this study. Eight radiation oncologists manually and independently delineated cardiac contours on the non-contrast CT by referring to the fused contrast CT and following the RTOG 1106 atlas contouring guideline. Fifteen regions of interest (ROIs) were delineated, including heart, four chambers, four coronary arteries, pulmonary artery and vein, inferior and superior vena cava, and ascending and descending aorta. Individual expert contours were fused using the simultaneous truth and performance level estimation (STAPLE) algorithm for each ROI and each patient. The fused contours became atlases for an in-house multi-atlas segmentation. Using leave-one-out test, we generated auto-segmented contours for each ROI and each patient. The auto-segmented contours were compared with the fused contours using the Dice similarity coefficient (DSC) and the mean surface distance (MSD). Results: Inter-observer variability was not obvious for heart, chambers, and aorta but was large for other structures that were not clearly distinguishable on CT image. The average DSC between individual expert contours and the fused contours were less than 50% for coronary arteries and pulmonary vein, and the average MSD were greater than 4.0 mm. The largest MSD of expert contours deviating from the fused contours was 2.5 cm. The mean DSC and MSD of auto-segmented contours were within one standard deviation of expert contouring variability except the right coronary artery. The coronary arteries, vena cava, and pulmonary vein had DSC<70% and MSD>3.0 mm. Conclusion: A set of cardiac atlases was created for cardiac automatic contouring, the accuracy of which was comparable to the variability in expert contouring. However, substantial modification may need

Positron emission tomography (PET) imaging has been used to provide additional information regarding patient tumor location, size, and staging for radiotherapy treatment planning purposes. This additional information reduces interobserver variability and produces more consistent contouring. It is well recognized that different contouring methodology for PET data results in different contoured volumes. The goal of this study was to compare the difference in PET contouring methods for 2 different treatment planning systems using a phantom dataset and a series of patient datasets. Contouring methodology was compared on the ADAC Pinnacle Treatment Planning System and the CMS XiO Treatment Planning System. Contours were completed on the phantom and patient datasets using a number of PET contouring methods—the standardized uptake value 2.5 method, 30%, 40%, and 50% of the maximum uptake method and the signal to background ratio method. Differences of >15% were observed for PET-contoured volumes between the different treatment planning systems for the same data and the same PET contouring methodology. Contoured volume differences between treatment planning systems were caused by differences in data formatting and display and the different contouring tools available. Differences in treatment planning system as well as contouring methodology should be considered carefully in dose-volume contouring and reporting, especially between centers that may use different treatment planning systems or those that have several different treatment planning systems

Robustness to obstacles is the most important factor necessary to achieve accurate tumor tracking without fiducial markers. Some high-density structures, such as bone, are enhanced on X-ray fluoroscopic images, which cause tumor mistracking. Tumor tracking should be performed by controlling "importance recognition": the understanding that soft-tissue is an important tracking feature and bone structure is unimportant. We propose a new real-time tumor-contouring method that uses deep learning with importance recognition control. The novelty of the proposed method is the combination of the devised random overlay method and supervised deep learning to induce the recognition of structures in tumor contouring as important or unimportant. This method can be used for tumor contouring because it uses deep learning to perform image segmentation. Our results from a simulated fluoroscopy model showed accurate tracking of a low-visibility tumor with an error of approximately 1 mm, even if enhanced bone structure acted as an obstacle. A high similarity of approximately 0.95 on the Jaccard index was observed between the segmented and ground truth tumor regions. A short processing time of 25 ms was achieved. The results of this simulated fluoroscopy model support the feasibility of robust real-time tumor contouring with fluoroscopy. Further studies using clinical fluoroscopy are highly anticipated.

The modelling of mass and activity transport in PHWR is of importance in predicting the build up of radiation field in and around the Primary Heat Transport system which will consequently help in planning the Dilute Chemical Decontamination and man rem budgeting. Modeling also helps in understanding the different parameters controlling the transport behaviour. Some of the important parameters include coolant chemistry like pH, physical parameters like temperature, the nature of the corrosion film and hence the effect of passivation techniques. VVER code for activity transport uses six nodes for the primary system and is essentially devised for stainless steel system. In the present work though based on this model, major modifications have been incorporated to suit the PHWR conditions. In the code, the PHT system of PHWR is suitably divided into 14 nodes, 5 in-core and 9 out of core nodes based on material and heat transfer properties. This paper describes the mechanisms involved in the various processes like generation of corrosion products, their release as well as their transport into the primary coolant, the activation of inactive corrosion product nuclides and the build up of radiation field due to 60 Co around the PHT system. (author)

Purpose: To investigate and validate the use of an independent deformable-based contouring algorithm for automatic verification of auto-contoured structures in the head and neck towards fully automated treatment planning. Methods: Two independent automatic contouring algorithms [(1) Eclipse’s Smart Segmentation followed by pixel-wise majority voting, (2) an in-house multi-atlas based method] were used to create contours of 6 normal structures of 10 head-and-neck patients. After rating by a radiation oncologist, the higher performing algorithm was selected as the primary contouring method, the other used for automatic verification of the primary. To determine the ability of the verification algorithm to detect incorrect contours, contours from the primary method were shifted from 0.5 to 2cm. Using a logit model the structure-specific minimum detectable shift was identified. The models were then applied to a set of twenty different patients and the sensitivity and specificity of the models verified. Results: Per physician rating, the multi-atlas method (4.8/5 point scale, with 3 rated as generally acceptable for planning purposes) was selected as primary and the Eclipse-based method (3.5/5) for verification. Mean distance to agreement and true positive rate were selected as covariates in an optimized logit model. These models, when applied to a group of twenty different patients, indicated that shifts could be detected at 0.5cm (brain), 0.75cm (mandible, cord), 1cm (brainstem, cochlea), or 1.25cm (parotid), with sensitivity and specificity greater than 0.95. If sensitivity and specificity constraints are reduced to 0.9, detectable shifts of mandible and brainstem were reduced by 0.25cm. These shifts represent additional safety margins which might be considered if auto-contours are used for automatic treatment planning without physician review. Conclusion: Automatically contoured structures can be automatically verified. This fully automated process could be used to

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure-ground segregation. Although previous studies have reported local contour features that evoke figure-ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure-ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure-ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure-ground perception with natural contours when the other cues coexist with equal probability including contradictory cases.

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure–ground segregation. Although previous studies have reported local contour features that evoke figure–ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure–ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure–ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure–ground perception with natural contours when the other cues coexist with equal probability including contradictory cases. PMID:26579057

Full Text Available A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure-ground segregation. Although previous studies have reported local contour features that evoke figure-ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural contour shapes. We performed similarity tests between local contours, and examined the contribution of the contour features to the perceptual similarities between the contours. The local contours were sampled from natural contours so that their distribution was uniform in the space composed of the three contour features. This sampling ensured the equal appearance frequency of the factors and a wide variety of contour shapes including those comprised of contradictory factors that induce figure in the opposite directions. This sampling from natural contours is advantageous in order to randomly pickup a variety of contours that satisfy a wide range of cue combinations. Multidimensional scaling analyses showed that the combinations of convexity, closure, and symmetry contribute to perceptual similarity, thus they are perceptual quantities. Second, we examined whether the three features contribute to local figure-ground perception. We performed psychophysical experiments to judge the direction of the figure along the local contours, and examined the contribution of the features to the figure-ground judgment. Multiple linear regression analyses showed that closure was a significant factor, but that convexity and symmetry were not. These results indicate that closure is dominant in the local figure-ground perception with natural contours when the other cues coexist with equal probability including contradictory cases.

A contour shape strongly influences the perceptual segregation of a figure from the ground. We investigated the contribution of local contour shape to figure–ground segregation. Although previous studies have reported local contour features that evoke figure–ground perception, they were often image features and not necessarily perceptual features. First, we examined whether contour features, specifically, convexity, closure, and symmetry, underlie the perceptual representation of natural cont...

A new method of analysis for presenting the possible operating space for steady state, non-ignited tokamak reactors is proposed. The method uses contours of reactor performance and plasma characteristics, fusion power gain, wall neutron flux, current drive power, etc., plotted on a two-dimensional grid, the axes of which are the plasma current I p and the normalized beta, β n = β/(I p /aB 0 ), to show possible operating points. These steady state operating contour plots are called SOPCONS. This technique is illustrated in an application to a design for the International Thermonuclear Experimental Reactor (ITER) with neutral beam, lower hybrid and bootstrap current drive. The utility of the SOPCON plots for pointing out some of the non-intuitive considerations in steady state reactor design is shown. (author). Letter-to-the-editor. 16 refs, 3 figs, 1 tab

This article introduces a novel approach to robust automatic detection of unstained living cells in bright-field (BF) microscope images with the goal of producing a target list for an automated microinjection system. The overall image analysis process is described and includes: preprocessing, ridge enhancement, image segmentation, shape analysis and injection point definition. The developed algorithm implements a new version of anisotropic contour completion (ACC) based on the partial differential equation (PDE) for heat diffusion which improves the cell segmentation process by elongating the edges only along their tangent direction. The developed ACC algorithm is equivalent to a dilation of the binary edge image with a continuous elliptic structural element that takes into account local orientation of the contours preventing extension towards normal direction. Experiments carried out on real images of 10 to 50 microm CHO-K1 adherent cells show a remarkable reliability in the algorithm along with up to 85% success for cell detection and injection point definition.

The application of the method of contour rotations to the solution of the Faddeev-Lovelace equations and the calculation of the break-up and stripping amplitudes in a system of three distinct particles is reviewed. A relationship between the masses of the particles is obtained, which permits the break-up amplitude to be calculated from a single iteration of the final integral equation. (Author) [pt

Laser contouring system capable of measuring relief profiles using a line-shaped laser beam with anisotropic magnification optics composed with two cylindrical lenses was developed. The anisotropic magnification optical system allows it to obtain higher resolution in the relief profile measurements. The image processing and 3-D display software are developed to reconstruct 3-D shape. The power supply of laser diode with adaptive current control circuit is designed. (author). 4 refs., 5 tabs., 33 figs.

Nutrient enrichment and excessive sediment loadings have contributed to the degradation of rivers, lakes and estuaries in North Carolina. The North Carolina Department of Environmental Quality (NCDEQ) has implemented several basin-wide nutrient and sediment management strategies, yet gaps remain in understanding the impact of these strategies given the complexities in quantifying the processes that govern the transport of nutrient and sediment. In particular, improved assessment of the status of nutrient and sediment loadings to lakes and estuaries throughout the state is needed, including characterizing their sources and describing the relative contributions of different areas. The NCDEQ Division of Mitigation Services (DMS) uses watershed planning to identify and prioritize the best locations to implement stream, wetland, and riparian-buffer restoration to improve water quality. To support better decision-making for watershed restoration activities we are developing a SPARROW (SPAtially Referenced Regressions On Watershed attributes) model framework specifically for North Carolina. The SPARROW analysis (developed by the U.S. Geological Survey) relates water-quality monitoring data to better understand the effects of human activities and natural processes on surface-water quality. The core of the model consists of using a nonlinear-regression equation to describe the non-conservative transport of contaminants from point and nonpoint sources on land to rivers, lakes and estuaries through the stream and river network. In this presentation, preliminary total Nitrogen, total Phosphorus, and Total Suspended Solids (TSS) NC-SPARROW models are described that illustrate the SPARROW modeling framework incorporating specific restoration datasets and activity metrics, such as extent of riparian buffer and easements.

Full Text Available This paper presents a system that automatically extracts the position of the eyeglasses and the accurate shape and size of the frame lenses in facial images. The novelty brought by this paper consists in three key contributions. The first one is an original model for representing the shape of the eyeglasses lens, using Fourier descriptors. The second one is a method for generating the search space starting from a finite, relatively small number of representative lens shapes based on Fourier morphing. Finally, we propose an accurate lens contour extraction algorithm using a multi-stage Monte Carlo sampling technique. Multiple experiments demonstrate the effectiveness of our approach.

Purpose: To quantify the effect of contouring variation on stereotactic radiosurgery plan quality metrics for brain metastases. Methods and Materials: Fourteen metastases, each contoured by 8 physicians, formed the basis of this study. A template-based dynamic conformal 5-arc dose distribution was developed for each of the 112 contours, and each dose distribution was applied to the 7 other contours in each patient set. Radiation Therapy Oncology Group (RTOG) plan quality metrics and the Paddick conformity index were calculated for each of the 896 combinations of dose distributions and contours. Results: The ratio of largest to smallest contour volume for each metastasis varied from 1.25 to 4.47, with a median value of 1.68 (n=8). The median absolute difference in RTOG conformity index between the value for the reference contour and the values for the alternative contours was 0.35. The variation of the range of conformity index for all contours for a given tumor varied with the tumor size. Conclusions: The high degree of interobserver contouring variation strongly suggests that peer review or consultation should be adopted to standardize tumor volume prescription. Observer confidence was not reflected in contouring consistency. The impact of contouring variability on plan quality metrics, used as criteria for clinical trial protocol compliance, was such that the category of compliance was robust to interobserver effects only 70% of the time

There has been a surge of recent interest in the role of anisotropy in interaction-induced phenomena in two-dimensional (2D) charged carrier systems. A fundamental question is how an anisotropy in the energy-band structure of the carriers at zero magnetic field affects the properties of the interacting particles at high fields, in particular of the composite fermions (CFs) and the fractional quantum Hall states (FQHSs). We demonstrate here tunable anisotropy for holes and hole-flux CFs confined to GaAs quantum wells, via applying in situ in-plane strain and measuring their Fermi wave vector anisotropy through commensurability oscillations. For strains on the order of 10^{-4} we observe significant deformations of the shapes of the Fermi contours for both holes and CFs. The measured Fermi contour anisotropy for CFs at high magnetic field (α_{CF}) is less than the anisotropy of their low-field hole (fermion) counterparts (α_{F}), and closely follows the relation α_{CF}=sqrt[α_{F}]. The energy gap measured for the ν=2/3 FQHS, on the other hand, is nearly unaffected by the Fermi contour anisotropy up to α_{F}∼3.3, the highest anisotropy achieved in our experiments.

Full Text Available Unmanned aerial vehicles (UAVs provide a flexible and low-cost solution for the acquisition of high-resolution data. The potential of high-resolution UAV imagery to create and update cadastral maps is being increasingly investigated. Existing procedures generally involve substantial fieldwork and many manual processes. Arguably, multiple parts of UAV-based cadastral mapping workflows could be automated. Specifically, as many cadastral boundaries coincide with visible boundaries, they could be extracted automatically using image analysis methods. This study investigates the transferability of gPb contour detection, a state-of-the-art computer vision method, to remotely sensed UAV images and UAV-based cadastral mapping. Results show that the approach is transferable to UAV data and automated cadastral mapping: object contours are comprehensively detected at completeness and correctness rates of up to 80%. The detection quality is optimal when the entire scene is covered with one orthoimage, due to the global optimization of gPb contour detection. However, a balance between high completeness and correctness is hard to achieve, so a combination with area-based segmentation and further object knowledge is proposed. The localization quality exhibits the usual dependency on ground resolution. The approach has the potential to accelerate the process of general boundary delineation during the creation and updating of cadastral maps.

Highlights: → A novel fractal dimension concept, based on Fourier spectrum, is proposed. → Computationally simple. Computational time smaller than conventional fractal methods. → Results are closer to Hausdorff-Besicovitch than conventional methods. → The method is more accurate and robustness to geometric operations and noise addition. - Abstract: This work proposes a novel technique for the numerical calculus of the fractal dimension of fractal objects which can be represented as a closed contour. The proposed method maps the fractal contour onto a complex signal and calculates its fractal dimension using the Fourier transform. The Fourier power spectrum is obtained and an exponential relation is verified between the power and the frequency. From the parameter (exponent) of the relation, is obtained the fractal dimension. The method is compared to other classical fractal dimension estimation methods in the literature, e.g., Bouligand-Minkowski, box-counting and classical Fourier. The comparison is achieved by the calculus of the fractal dimension of fractal contours whose dimensions are well-known analytically. The results showed the high precision and robustness of the proposed technique.

Results of three-dimensional (3D) time-dependent Hartree--Fock (TDHF) calculations are presented. The assumptions used in the calculations are summarized. The first reaction considered is /sup 16/O + /sup 16/O at 105 MeV (lab); isodensity contours integrated perpendicular to the reaction plane are shown for several impact parameters as a function of time. Trajectories are also shown, and the kinetics of the reaction is discussed; several other energies were also examined. Most of the deeply inelastic scattering seems to come from small impact parameters. Density contours and trajectories are next shown for /sup 40/Ca + /sup 40/Ca at 278 MeV (lab). Finally, density contours are shown for asymmetric systems: /sup 4/He + /sup 16/O at l = 5 h-bar and 50 MeV (lab) and /sup 16/O + /sup 40/Ca at l = 20, 40, 60, 80 h-bar and 315 MeV (lab). The light fragment seems to maintain the same average number of nucleons with which it started. 25 figures. (RWR)

Full Text Available Triangular channels have different applications in many water and wastewater engineering problems. For this purpose investigating hydraulic characteristics of flow in these sections has great importance. Researchers have presented different prediction methods for the velocity contours in prismatic sections. Most proposed methods are not able to consider the effect of walls roughness, the roughness distribution and secondary flows. However, due to complexity and nonlinearity of velocity contours in open channel flow, there is no simple relationship that can be fully able to exactly draw the velocity contours. In this paper an efficient approach for modeling velocity contours in triangular open channels with non-uniform roughness distributions by Adaptive Neuro-Fuzzy Inference System (ANFIS has been suggested. For training and testing model, the experimental data including 1703 data in triangular channels with geometric symmetry and non-uniform roughness distributions have been used. Comparing experimental results with predicted values by model indicates that ANFIS model is capable to be used in simulation of local velocity and determining velocity contours and the independent evaluation showed that the calculated values of discharge and depth-averaged velocity from model information are precisely in conformity with experimental values.

Purpose: Precise contour delineation of tumor targets and critical structures from CT simulations is essential for accurate radiotherapy (RT) treatment planning. However, manual and automatic delineation processes can be error prone due to limitations in imaging techniques and individual anatomic variability. Tedious and laborious manual verification is hence needed. This study develops a general framework for automatically assessing RT contours for head-neck cancer patients using geometric attribute distribution models (GADMs). Methods: Geometric attributes (centroid and volume) were computed from physician-approved RT contours of 29 head-neck patients. Considering anatomical correlation between neighboring structures, the GADM for each attribute was trained to characterize intra- and interpatient structure variations using principal component analysis. Each trained GADM was scalable and deformable, but constrained by the principal attribute variations of the training contours. A new hierarchical model adaptation algorithm was utilized to assess the RT contour correctness for a given patient. Receiver operating characteristic (ROC) curves were employed to evaluate and tune system parameters for the training models. Results: Experiments utilizing training and non-training data sets with simulated contouring errors were conducted to validate the framework performance. Promising assessment results of contour normality/abnormality for the training contour-based data were achieved with excellent accuracy (0.99), precision (0.99), recall (0.83), and F-score (0.97), while corresponding values of 0.84, 0.96, 0.83, and 0.9 were achieved for the non-training data. Furthermore, the areas under the ROC curves were above 0.9, validating the accuracy of this test. Conclusion: The proposed framework can reliably identify contour normality/abnormality based upon intra- and inter-structure constraints derived from clinically-approved contours. It also allows physicians to

Process modeling of activated sludge flocculation and sedimentation reviews consider the activated sludge floc characteristics such as: morphology viable and non-viable cell ratio density and water content, bio flocculation and its kinetics were studied considering the characteristics of bio flocculation and explaining theory of Divalent Cation Bridging which describes the major role of cations in bio flocculation. Activated sludge flocculation process modeling was studied considering mass transfer limitations from Clifft and Andrew, 1981, Benefild and Molz 1983 passing Henze 1987, until Tyagi 1996 and G. Ibrahim et aI. 2002. Models of aggregation and breakage of flocs were studied by Spicer and Pratsinis 1996,and Biggs 2002 Size distribution of floes influences mass transfer and biomass separation in the activated sludge process. Therefore, it is of primary importance to establish the role of specific process operation factors, such as sludge loading dynamic sludge age and dissolved oxygen, on this distribution with special emphasis on the formation of primary particles

Full Text Available By using active and participatory methods it is hoped that pupils will not only come to a deeper understanding of the issues involved, but also that their motivation will be heightened. Pupil involvement in their learning is essential. Moreover, by using a variety of teaching techniques, we can help students make sense of the world in different ways, increasing the likelihood that they will develop a conceptual understanding. The teacher must be a good facilitator, monitoring and supporting group dynamics. Modeling is an instructional strategy in which the teacher demonstrates a new concept or approach to learning and pupils learn by observing. In the teaching of biology the didactic materials are fundamental tools in the teaching-learning process. Reading about scientific concepts or having a teacher explain them is not enough. Research has shown that modeling can be used across disciplines and in all grade and ability level classrooms. Using this type of instruction, teachers encourage learning.

Full Text Available Activity-Based-Model (ABC is used for the purpose of significant improvement for overhead accounting systems by providing the best information required for managerial decision. This pa-per discusses implacability of ABC technique on inventory valuation as a management account-ing innovation. In order to prove the applicability of ABC for inventory control a material driven medium-sized and privately owned company from engineering (iron and steel industry is select-ed and by analysis of its production process and its material dependency and use of indirect in-ventory, an ABC model is explored for better inventory control. The case revealed that the ne-cessity of ABC in the area of inventory control is significant. The company is not only able to increase its quality of decision but also it can significantly analyze its cost of direct material cost, valuation of direct material and use its implications for better decision making.

Time contour expression of limited range phenomena on stack chart is examined for further improvement on the result of the ultimate interpretation in the seismic reflection survey. The policy is made clear from the beginning that local phenomena are to be discussed, and data prior CMP stacking is interpreted in detail. For this purpose, it is effective to make use of the time contour expression in the midpoint-offset plane simultaneously with the CMP and COP panels. For the review of data prior to CMP stacking, it is convenient to use the CMP (CDP) stacking chart in which the data is arranged methodically. In this chart, all the channels which are crude data prior to stacking are plotted on midpoint-offset coordinates, which plane is called the MOD (Midpoint Offset Domain) panel. Various panels can be chosen unrestrictedly, and their mutual relations can be easily grasped. When data points are given a time axis, they can be expressed in a time contour. Studies are conducted about the underground structure, multiple reflection paths divided by it, and characteristics of detour reflection attributable to faults. 4 refs., 9 figs.

Contour interpolation is a perceptual process that fills-in missing edges on the basis of how surrounding edges (inducers) are spatiotemporally related. Cognitive encapsulation refers to the degree to which perceptual mechanisms act in isolation from beliefs, expectations, and utilities (Pylyshyn, 1999). Is interpolation encapsulated from belief? We addressed this question by having subjects discriminate briefly-presented, partially-visible fat and thin shapes, the edges of which either induced or did not induce illusory contours (relatable and non-relatable conditions, respectively). Half the trials in each condition incorporated task-irrelevant distractor lines, known to disrupt the filling-in of contours. Half of the observers were told that the visible parts of the shape belonged to a single thing (group strategy); the other half were told that the visible parts were disconnected (ungroup strategy). It was found that distractor lines strongly impaired performance in the relatable condition, but minimally in the non-relatable condition; that strategy did not alter the effects of the distractor lines for either the relatable or non-relatable stimuli; and that cognitively grouping relatable fragments improved performance whereas cognitively grouping non-relatable fragments did not. These results suggest that 1) filling-in effects during illusory contour formation cannot be easily removed via strategy; 2) filling-in effects cannot be easily manufactured from stimuli that fail to elicit interpolation; and 3) actively grouping fragments can readily improve discrimination performance, but only when those fragments form interpolated contours. Taken together, these findings indicate that discriminating filled-in shapes depends on strategy but filling-in itself may be encapsulated from belief. PMID:22440789

Although several activity-based models made the transition to practice in recent years, modeling dynamic activity generation and especially, the mechanisms underlying activity generation are not well incorporated in the current activity-based models. For instance, current models assume that

Although several activity-based models made the transition to practice in recent years, modelling dynamic activity generation and especially, the mechanisms underlying activity generation are not well incorporated in the current activity-based models. For example, current models assume that

Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagation was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in contour propagation.

Purpose: To compare the contour propagation accuracy of two deformable image registration (DIR) algorithms in the Raystation treatment planning system – the “Hybrid” algorithm based on image intensities and anatomical information; and the “Biomechanical” algorithm based on linear anatomical elasticity and finite element modeling. Methods: Both DIR algorithms were used for CT-to-CT deformation for 20 lung radiation therapy patients that underwent treatment plan revisions. Deformation accuracy was evaluated using landmark tracking to measure the target registration error (TRE) and inverse consistency error (ICE). The deformed contours were also evaluated against physician drawn contours using Dice similarity coefficients (DSC). Contour propagation was qualitatively assessed using a visual quality score assigned by physicians, and a refinement quality score (0 0.9 for lungs, > 0.85 for heart, > 0.8 for liver) and similar qualitative assessments (VQS < 0.35, RQS > 0.75 for lungs). When anatomical structures were used to control the deformation, the DSC improved more significantly for the biomechanical DIR compared to the hybrid DIR, while the VQS and RQS improved only for the controlling structures. However, while the inclusion of controlling structures improved the TRE for the hybrid DIR, it increased the TRE for the biomechanical DIR. Conclusion: The hybrid DIR was found to perform slightly better than the biomechanical DIR based on lower TRE while the DSC, VQS, and RQS studies yielded comparable results for both. The use of controlling structures showed considerable improvement in the hybrid DIR results and is recommended for clinical use in

The most important requirement for high-level waste glass acceptance for disposal in a geological repository is the chemical durability, expressed as a glass dissolution rate. During the early stages of glass dissolution in near static conditions that represent a repository disposal environment, a gel layer resembling a membrane forms on the glass surface through which ions exchange between the glass and the leachant. The hydrated gel layer exhibits acid/base properties which are manifested as the pH dependence of the thickness and nature of the gel layer. The gel layer has been found to age into either clay mineral assemblages or zeolite mineral assemblages. The formation of one phase preferentially over the other has been experimentally related to changes in the pH of the leachant and related to the relative amounts of Al +3 and Fe +3 in a glass. The formation of clay mineral assemblages on the leached glass surface layers ,lower pH and Fe +3 rich glasses, causes the dissolution rate to slow to a long-term steady state rate. The formation of zeolite mineral assemblages ,higher pH and Al +3 rich glasses, on leached glass surface layers causes the dissolution rate to increase and return to the initial high forward rate. The return to the forward dissolution rate is undesirable for long-term performance of glass in a disposal environment. An investigation into the role of glass stoichiometry, in terms of the quasi-crystalline mineral species in a glass, has shown that the chemistry and structure in the parent glass appear to control the activated surface complexes that form in the leached layers, and these mineral complexes ,some Fe +3 rich and some Al +3 rich, play a role in whether or not clays or zeolites are the dominant species formed on the leached glass surface. The chemistry and structure, in terms of Q distributions of the parent glass, are well represented by the atomic ratios of the glass forming components. Thus, glass dissolution modeling using simple

Full text: Inter-observer variability in anatomical contouring is the biggest contributor to uncertainty in radiation treatment planning. Contouring studies are frequently performed to investigate the differences between multiple contours on common datasets. There is, however, no widely accepted method for contour comparisons. The purpose of this study is to review the literature on contouring studies in the context of radiation oncology, with particular consideration of the contouring comparison methods they employ. A literature search, not limited by date, was conducted using Medline and Google Scholar with key words; contour, variation, delineation, inter/intra observer, uncertainty and trial dummy-run. This review includes a description of the contouring processes and contour comparison metrics used. The use of different processes and metrics according to tumour site and other factors were also investigated with limitations described. A total of 69 relevant studies were identified. The most common tumour sites were prostate (26), lung (10), head and neck cancers (8) and breast (7).The most common metric of comparison was volume used 59 times, followed by dimension and shape used 36 times, and centre of volume used 19 times. Of all 69 publications, 67 used a combination of metrics and two used only one metric for comparison. No clear relationships between tumour site or any other factors that may in Auence the contouring process and the metrics used to compare contours were observed from the literature. Further studies are needed to assess the advantages and disadvantages of each metric in various situations.

Purpose: The purpose of this study was to develop a radiation therapy (RT) contouring atlas and recommendations for women with postoperative and locally advanced vulvar carcinoma. Methods and Materials: An international committee of 35 expert gynecologic radiation oncologists completed a survey of the treatment of vulvar carcinoma. An initial set of recommendations for contouring was discussed and generated by consensus. Two cases, 1 locally advanced and 1 postoperative, were contoured by 14 physicians. Contours were compared and analyzed using an expectation-maximization algorithm for simultaneous truth and performance level estimation (STAPLE), and a 95% confidence interval contour was developed. The level of agreement among contours was assessed using a kappa statistic. STAPLE contours underwent full committee editing to generate the final atlas consensus contours. Results: Analysis of the 14 contours showed substantial agreement, with kappa statistics of 0.69 and 0.64 for cases 1 and 2, respectively. There was high specificity for both cases (≥99%) and only moderate sensitivity of 71.3% and 64.9% for cases 1 and 2, respectively. Expert review and discussion generated consensus recommendations for contouring target volumes and treatment for postoperative and locally advanced vulvar cancer. Conclusions: These consensus recommendations for contouring and treatment of vulvar cancer identified areas of complexity and controversy. Given the lack of clinical research evidence in vulvar cancer radiation therapy, the committee advocates a conservative and consistent approach using standardized recommendations.

Purpose: The purpose of this study was to develop a radiation therapy (RT) contouring atlas and recommendations for women with postoperative and locally advanced vulvar carcinoma. Methods and Materials: An international committee of 35 expert gynecologic radiation oncologists completed a survey of the treatment of vulvar carcinoma. An initial set of recommendations for contouring was discussed and generated by consensus. Two cases, 1 locally advanced and 1 postoperative, were contoured by 14 physicians. Contours were compared and analyzed using an expectation-maximization algorithm for simultaneous truth and performance level estimation (STAPLE), and a 95% confidence interval contour was developed. The level of agreement among contours was assessed using a kappa statistic. STAPLE contours underwent full committee editing to generate the final atlas consensus contours. Results: Analysis of the 14 contours showed substantial agreement, with kappa statistics of 0.69 and 0.64 for cases 1 and 2, respectively. There was high specificity for both cases (≥99%) and only moderate sensitivity of 71.3% and 64.9% for cases 1 and 2, respectively. Expert review and discussion generated consensus recommendations for contouring target volumes and treatment for postoperative and locally advanced vulvar cancer. Conclusions: These consensus recommendations for contouring and treatment of vulvar cancer identified areas of complexity and controversy. Given the lack of clinical research evidence in vulvar cancer radiation therapy, the committee advocates a conservative and consistent approach using standardized recommendations.

The reorganization of the national health system (SNS), enforces reflection and transformation on medical education in clinical contexts. The study presents an educational model to develop entrusted professionals activities (MEDAPROC) to train human resources in health with reliable knowledge, skills and attitudes to work in the shifting scenario of the SNS. The paper discusses international and national documents on skills in medicine. Based on the analysis of 8 domains, 50 skills and 13 entrusted professional activities (RPA) proposed by the Association of the American Medical College (AAMC) we propose a curriculum design, with the example of the undergraduate program of Gynecology and Obstetrics, with the intention to advance to internship and residency in a continuum that marks milestones and clinical practices. The pedagogical design of MEDAPROC was developed within three areas: 1) proposal of the AAMC; 2) curricular content of programs in pre and postgraduate education 3) organization of the daily agenda with academic mechanisms to develop the competencies, cover program items and develop clinical practice in deliberate learning activities, as well as milestones. The MEDAPROC offers versatility, student mobility and curricular flexibility in a system planed by academic units in diverse clinical settings.

Active brazes have been used for many years to produce bonds between metal and ceramic objects. By including a relatively small of a reactive additive to the braze one seeks to improve the wetting and spreading behavior of the braze. The additive modifies the substrate, either by a chemical surface reaction or possibly by alloying. By its nature, the joining process with active brazes is a complex nonequilibrium non-steady state process that couples chemical reaction, reactant and product diffusion to the rheology and wetting behavior of the braze. Most of the these subprocesses are taking place in the interfacial region, most are difficult to access by experiment. To improve the control over the brazing process, one requires a better understanding of the melting of the active braze, rate of the chemical reaction, reactant and product diffusion rates, nonequilibrium composition-dependent surface tension as well as the viscosity. This report identifies ways in which modeling and theory can assist in improving our understanding.

These notes have grown from a series of seminars given at Leeds between 1972 and 1975. They represent an attempt to gather together the different kinds of model which have been proposed to account for the stochastic activity of neurones, and to provide an introduction to this area of mathematical biology. A striking feature of the electrical activity of the nervous system is that it appears stochastic: this is apparent at all levels of recording, ranging from intracellular recordings to the electroencephalogram. The chapters start with fluctuations in membrane potential, proceed through single unit and synaptic activity and end with the behaviour of large aggregates of neurones: L have chgaen this seque~~e\\/~~';uggest that the interesting behaviourr~f :the nervous system - its individuality, variability and dynamic forms - may in part result from the stochastic behaviour of its components. I would like to thank Dr. Julio Rubio for reading and commenting on the drafts, Mrs. Doris Beighton for producing the fin...

The concept of the active state model (ASM) is an architecture for the development of advanced integrated fault-detection-and-isolation (FDI) systems for robotic land vehicles, pilotless aircraft, exploratory spacecraft, or other complex engineering systems that will be capable of autonomous operation. An FDI system based on the ASM concept would not only provide traditional diagnostic capabilities, but also integrate the FDI system under a unified framework and provide mechanism for sharing of information between FDI subsystems to fully assess the overall health of the system. The ASM concept begins with definitions borrowed from psychology, wherein a system is regarded as active when it possesses self-image, self-awareness, and an ability to make decisions itself, such that it is able to perform purposeful motions and other transitions with some degree of autonomy from the environment. For an engineering system, self-image would manifest itself as the ability to determine nominal values of sensor data by use of a mathematical model of itself, and selfawareness would manifest itself as the ability to relate sensor data to their nominal values. The ASM for such a system may start with the closed-loop control dynamics that describe the evolution of state variables. As soon as this model was supplemented with nominal values of sensor data, it would possess self-image. The ability to process the current sensor data and compare them with the nominal values would represent self-awareness. On the basis of self-image and self-awareness, the ASM provides the capability for self-identification, detection of abnormalities, and self-diagnosis.

: Intraoperative contouring of long bridging plates for stabilization of flail chest injuries is difficult and time consuming. This study implemented for the first time biometric parameters to derive anatomically contoured rib plates. These plates were tested on a range of cadaveric ribs to quantify plate fit and to extract a best-fit plating configuration. : Three left and three right rib plates were designed, which accounted for anatomic parameters required when conforming a plate to the rib surface. The length lP over which each plate could trace the rib surface was evaluated on 109 cadaveric ribs. For each rib level 3-9, the plate design with the highest lP value was extracted to determine a best-fit plating configuration. Furthermore, the characteristic twist of rib surfaces was measured on 49 ribs to determine the surface congruency of anatomic plates with a constant twist. : The tracing length lP of the best-fit plating configuration ranged from 12.5 cm to 14.7 cm for ribs 3-9. The corresponding range for standard plates was 7.1-13.7 cm. The average twist of ribs over 8-cm, 12-cm, and 16-cm segments was 8.3 degrees, 20.6 degrees, and 32.7 degrees, respectively. The constant twist of anatomic rib plates was not significantly different from the average rib twist. : A small set of anatomic rib plates can minimize the need for intraoperative plate contouring for fixation of ribs 3-9. Anatomic rib plates can therefore reduce the time and complexity of flail chest stabilization and facilitate spanning of flail segments with long plates.

The optimum conditions for acid activation of diatomite for maximizing bleaching efficiency of the diatomite in sun flower oil treatment were studied. Box-Behnken experimental design combining with response surface modeling (RSM) and quadratic programming (QP) was employed to obtain the optimum conditions of three independent variables (acid concentration, activation time and solid to liquid) for acid activation of diatomite. The significance of independent variables and their interactions were tested by means of the analysis of variance (ANOVA) with 95 % confidence limits (α = 0.05). The optimum values of the selected variables were obtained by solving the quadratic regression model, as well as by analyzing the response surface contour plots. The experimental conditions at this global point were determined to be acid concentration = 8.963 N, activation time = 11.9878 h, and solid to liquid ratio = 221.2113 g/l, the corresponding bleaching efficiency was found to be about 99 %.

Full Text Available OBJECTIVES: Intonation may serve as a cue for facilitated recognition and processing of spoken words and it has been suggested that the pitch contour of spoken words is implicitly remembered. Thus, using the repetition suppression (RS effect of BOLD-fMRI signals, we tested whether the same spoken words are differentially processed in language and auditory brain areas depending on whether or not they retain an arbitrary intonation pattern. EXPERIMENTAL DESIGN: Words were presented repeatedly in three blocks for passive and active listening tasks. There were three prosodic conditions in each of which a different set of words was used and specific task-irrelevant intonation changes were applied: (i All words presented in a set flat monotonous pitch contour (ii Each word had an arbitrary pitch contour that was set throughout the three repetitions. (iii Each word had a different arbitrary pitch contour in each of its repetition. PRINCIPAL FINDINGS: The repeated presentations of words with a set pitch contour, resulted in robust behavioral priming effects as well as in significant RS of the BOLD signals in primary auditory cortex (BA 41, temporal areas (BA 21 22 bilaterally and in Broca's area. However, changing the intonation of the same words on each successive repetition resulted in reduced behavioral priming and the abolition of RS effects. CONCLUSIONS: Intonation patterns are retained in memory even when the intonation is task-irrelevant. Implicit memory traces for the pitch contour of spoken words were reflected in facilitated neuronal processing in auditory and language associated areas. Thus, the results lend support for the notion that prosody and specifically pitch contour is strongly associated with the memory representation of spoken words.

In this paper we consider the problems encountered when applying snake models to detect the contours of the carpal bones in 3-D MR images of the wrist. In order to improve the performance of the original snake model introduced by Kass [1], we propose a new image force based on one-dimensional (1-D)

Arrays of supersonic, high momentum flux plasma jets can be used as standoff compression drivers for generating spherically imploding plasma liners for driving magneto-inertial fusion, hence the name plasma-jet-driven MIF (PJMIF). HyperV developed linear plasma jets for the Plasma Liner Experiment (PLX) at LANL where two guns were successfully tested. Further development at HyperV resulted in achieving the PLX goal of 8000 μg at 50 km/s. Prior work on contoured-gap coaxial guns demonstrated an approach to control the blowby instability and achieved substantial performance improvements. For future plasma liner experiments we propose to use contoured-gap coaxial guns with small Minirailgun injectors. We will describe such a gun for a 60-gun plasma liner experiment. Discussion topics will include impurity control, plasma jet symmetry and topology (esp. related to uniformity and compactness), velocity capability, and techniques planned for achieving gun efficiency of >50% using tailored impedance matched pulse forming networks. Mach2 and UAH SPH code simulations will be included. Work supported by US DOE DE-FG02-05ER54810.

Positron Emission Tomography (PET) is a nuclear medicine imaging technique that permits to analyze, in three dimensions, the physiological processes in vivo. One of the areas where PET has demonstrated its advantages is in the staging of lung cancer, where it offers better sensitivity and specificity than other techniques such as CT. On the other hand, accurate segmentation, an important procedure for Computer Aided Diagnostics (CAD) and automated image analysis, is a challenging task given the low spatial resolution and the high noise that are intrinsic characteristics of PET images. This work presents an algorithm for the segmentation of lungs in PET images, to be used in CAD and group analysis in a large patient database. The lung boundaries are automatically extracted from a PET volume through the application of a marker-driven watershed segmentation procedure which is robust to the noise. In order to test the effectiveness of the proposed method, we compared the segmentation results in several slices using our approach with the results obtained from manual delineation. The manual delineation was performed by nuclear medicine physicians that used a software routine that we developed specifically for this task. To quantify the similarity between the contours obtained from the two methods, we used figures of merit based on region and also on contour definitions. Results show that the performance of the algorithm was similar to the performance of human physicians. Additionally, we found that the algorithm-physician agreement is similar (statistically significant) to the inter-physician agreement.

While much is known about the specialized, parallel processing streams of low-level vision that extract primary visual cues, there is only limited knowledge about the dynamic interactions between them. How are the fragments, caught by local analyzers, assembled together to provide us with a unified percept? How are local discontinuities in texture, motion or depth evaluated with respect to object boundaries and surface properties? These questions are presented within the framework of orientation-specific spatial interactions of early vision. Key observations of psychophysics, anatomy and neurophysiology on interactions of various spatial and temporal ranges are reviewed. Aspects of the functional architecture and possible neural substrates of local orientation-specific interactions are discussed, underlining their role in the integration of information across the visual field, and particularly in contour integration. Examples are provided demonstrating that global context, such as contour closure and figure-ground assignment, affects these local interactions. It is illustrated that figure-ground assignment is realized early in visual processing, and that the pattern of early interactions also brings about an effective and sparse coding of visual shape. Finally, it is concluded that the underlying functional architecture is not only dynamic and context dependent, but the pattern of connectivity depends as much on past experience as on actual stimulation.

We measured the difference threshold for contour curvature in iconic memory by using the cued discrimination method. The study stimulus consisting of 2 to 6 curved contours was briefly presented in the fovea, followed by two lines as cues. Subjects discriminated the curvature of two cued curves. The cue delays were 0 msec. and 300 msec. in Exps. 1 and 2, respectively, and 50 msec. before the study offset in Exp. 3. Analysis of data from Exps. 1 and 2 showed that the Weber fraction rose monotonically with the increase in set size. Clear set-size effects indicate that iconic memory has a limited capacity. Moreover, clear set-size effect in Exp. 3 indicates that perception itself has a limited capacity. Larger set-size effects in Exp. 1 than in Exp. 3 suggest that iconic memory after perceptual process has limited capacity. These properties of iconic memory at threshold level are contradictory to the traditional view that iconic memory has a high capacity both at suprathreshold and categorical levels.

Many tasks involve the fine manipulation of objects despite limited visual feedback. In such scenarios, tactile and proprioceptive feedback can be leveraged for task completion. We present an approach for real-time haptic perception and decision-making for a haptics-driven, functional contour-following task: the closure of a ziplock bag. This task is challenging for robots because the bag is deformable, transparent, and visually occluded by artificial fingertip sensors that are also compliant. A deep neural net classifier was trained to estimate the state of a zipper within a robot's pinch grasp. A Contextual Multi-Armed Bandit (C-MAB) reinforcement learning algorithm was implemented to maximize cumulative rewards by balancing exploration versus exploitation of the state-action space. The C-MAB learner outperformed a benchmark Q-learner by more efficiently exploring the state-action space while learning a hard-to-code task. The learned C-MAB policy was tested with novel ziplock bag scenarios and contours (wire, rope). Importantly, this work contributes to the development of reinforcement learning approaches that account for limited resources such as hardware life and researcher time. As robots are used to perform complex, physically interactive tasks in unstructured or unmodeled environments, it becomes important to develop methods that enable efficient and effective learning with physical testbeds.

Unmanned Aerial Vehicles (UAV) have been widely used for Digital Elevation Model (DEM) generation in geographic applications. This paper proposes a novel framework of generating DEM from UAV images. It starts with the generation of the point clouds by image matching, where the flight control data are used as reference for searching for the corresponding images, leading to a significant time saving. Besides, a set of ground control points (GCP) obtained from field surveying are used to transform the point clouds to the user's coordinate system. Following that, we use a multi-feature based supervised classification method for discriminating non-ground points from ground ones. In the end, we generate DEM by constructing triangular irregular networks and rasterization. The experiments are conducted in the east of Jilin province in China, which has been suffered from soil erosion for several years. The quality of UAV based DEM (UAV-DEM) is compared with that generated from contour interpolation (Contour-DEM). The comparison shows a higher resolution, as well as higher accuracy of UAV-DEMs, which contains more geographic information. In addition, the RMSE errors of the UAV-DEMs generated from point clouds with and without GCPs are ±0.5 m and ±20 m, respectively.

The paper describes in general the contouring algorithm for two dimensional projection of aeroradiometric data and considers not only irregularly spaced flight lines but also solves the other problems related to voluminous data acquired during the airborne surveys. Several simple logics have been described for drawing the contours using scan method and taking care of annotations, identification marking, geographical locations, map size, contour density for visual distinctness and many such problems which may arise during contouring. The present paper also discusses various possibilities of contour line segments in the mini-grid and the criterion for selection of suitable segments has been described in detail. A novel approach to avoid the crossing of contours or missing data is also briefly discussed. The simplicity of the algorithm is mentioned for its ready implementation or any computer/plotter. (author). 8 refs., 8 figs

Contour detection is an important step in information extraction from nuclear medicine images. In order to perform accurate quantitative studies in single photon emission computed tomography (SPECT) a new procedure is described which can rapidly derive the best fit contour of an attenuated medium. Some authors evaluate the influence of the detected contour on the reconstructed images with various attenuation correction techniques. Most of the methods are strongly affected by inaccurately detected contours. This approach uses the Compton window to redetermine the convex contour: It seems to be simpler and more practical in clinical SPECT studies. The main advantages of this procedure are the high speed of computation, the accuracy of the contour found and the programme's automation. Results obtained using computer simulated and real phantoms or clinical studies demonstrate the reliability of the present algorithm. (orig.)

In this paper, a 2-dimensional rod-stabilized V-shaped flame is simulated using contour advection with surgery as well as the random vortex method. Effects of turbulence on various quantities, such as flame brush thickness and flame surface density, are investigated. The flame surface density S is estimated using the Bray-Moss-Libby formulation, which involves the use of a mean orientation factor {sigma}{sub c}. As a comparison, values of S are also obtained using Shepherd's model, which employs the values of mean flame surface area and mean flame length. Local flame structure is characterized in terms of turbulent flame brush, orientation factor, and flame surface density. Profiles of S obtained using the two different models are compared and show that discrepancy is more evident with increasing turbulence intensity. (author)

Biometric is a pattern recognition system which is used for automatic recognition of persons based on characteristics and features of an individual. Face recognition with high recognition rate is still a challenging task and usually accomplished in three phases consisting of face detection, feature extraction, and expression classification. Precise and strong location of trait point is a complicated and difficult issue in face recognition. Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. Furthermore, as the improvement of ASM, Active Appearance Models algorithm (AAM) is proposed to extracts both shape and texture of specified object simultaneously. In this paper we give more details about the two algorithms and give the results of experiments, testing their performance on one dataset of faces. We found that the ASM is faster and gains more accurate trait point location than the AAM, but the AAM gains a better match to the texture.

The area of isodensity contours in a smoothed density field can be measured by the contour-crossing statistic N1, the number of times per unit length that a line drawn through the density field pierces an isodensity contour. The contour-crossing statistic distinguishes between Gaussian and non-Gaussian fields and provides a measure of the effective slope of the power spectrum. The statistic is easy to apply and can be used on pencil beams and slices as well as on a three-dimensional field. 10 references

The description of patient contours and internal structures by means of truncated Fourier series can be extended to continuous contours of arbitrary shape and location by expressing the x and z Cartesian coordinates of the contour as independent Fourier series in a parameter t. An analytic equation for the intersection of the contour and a ray line is then written as an equation in the parameter t. The equation can be solved using numerical methods yielding the Cartesian coordinates of the intersection point directly

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the “contour” to that of “inside and outside”, or, masks, allowing for easy mul...

Full Text Available This paper presents a new method for solving the problem of utilizing the LiDAR data to extract the building contour line. For detection of the edge points between the building test points by using the least squares fitting to get the edge line of buildings and give the weight determining of the building of edge line slope depend on the length of the edge line. And then get the weighted mean of the positive and negative slope of the building edge line. Based on the structure of the adjacent edge perpendicular hypothesis, regularization processing to extract the edge of the skeleton line perpendicular. The experiments show that the extracted building edges have the good accuracy and have the good applicability in complex urban areas.

Despite a compelling body of published research on the nature of provider volume and clinical outcomes, healthcare executives and policymakers have not managed to develop and implement systems that are useful in directing patients to higher volume providers via selective referral or avoidance. A specialized data warehouse application, utilizing hospital discharge data linked to physician biographical information, allows detailed analysis of physician and hospital volume and the resulting pattern (contour) of related outcomes such as mortality, complications, and medical errors. The approach utilizes a historical repository of hospital discharge data in which the outcomes of interest, important patient characteristics and risk factors used in severity-adjusting of the outcomes are derived from the coding structure of the data.

Quantitative CT was one method used to assess changes in density and area of thigh muscles in paraplegics before and after aerobic leg training. Muscle density and area were measured from the CT image by an automatic contouring algorithm. In the first three patients, total muscle density increased from 11.5% to 18.3% and area increased from 18.3% to 31.3%. In one patient who did not comply with the exercise regimen, only a 10% increase in muscle density and area was detected. This CT program is valuable in the assessment of composition and alteration of limb musculature in the treatment and follow-up of muscular disorders

T 1 -weighted MR images of Legg-Calve-Perthes disease (LCPD) were classified into three groups on the basis of radiographic stage, and morphological differentiation for staging was attempted. In the stage of fragmentation, both enlargement and flattening of the cartilaginous contour surrounding the epiphysis could be recognized on MRI, and the growth plate showed more curvature than normal. This produced flattening of the epiphysis in the shape of a crescent. We confirmed these findings using four indices for the measurement of cartilaginous outline, and the stage of avascular necrosis and fragmentation could be clearly differentiated. Cartilaginous deformities on MRI are very useful for differentiating between the stage of avascular necrosis and fragmentation. (author)

Irradiated human cartilage has been found to be a superior implant material for correction of contour defects; however, availability problems have prevented this material from gaining wide acceptance. Implantation of processed irradiated bovine cartilage in primates and rabbits, as described here, provides strong evidence that this material performs like irradiated allograft cartilage antigenically and has certain cosmetic advantages over allograft cartilage. Our studies in primates have shown that there is no systemically measurable antibody-antigen reaction, either cellular or noncellular, to irradiated processed bovine cartilage. Neither primary nor second-set provocative implantations produced any measurable rejection. In rabbits, composite grafts of two pieces of irradiated bovine cartilage adjacent to each other were also well tolerated, with no measurable absorption and with capsule formation typical of a foreign body reaction to an inert object

Full Text Available Contours in the CSIR Supersonic Wind Tunnel B Vallabha,b and BW Skewsa Received 17 February 2017, in revised form 23 June 2017 and accepted 25 June 2017 R & D Journal of the South African Institution of Mechanical Engineering 2017, 33, 32-41 http... with the Sivellsâ nozzle design method and the method of characteristics technique to design the nozzle profiles for the full supersonic Mach number range ðð â€ ðŽðŽ â€ ðð.5 of the facility. Automatic computation was used for the profile...

The holes superconducting coupling with the pair high summarized pulse and the relative motion low pulses is considered with an account of the quasi-two-dimensional electron structure of the HTSC-cuprates with the clearly-pronounced nesting of the Fermi contour. The superconducting energy gap and the condensation energy are determined and their dependences on the doping level are qualitatively studied. It is shown that the energy gap takes place in some holes concentration area, limited on both sides. The superconducting state, whereby the condensation energy is positive, originates in the more narrower doping interval inside this area. The hole pair redistribution in the pulse space constitutes the cause of the superconducting state origination by the holes repulsive screened Coulomb interaction. The coupling mechanism discussed hereby, males it possible to explain qualitatively not only the phase diagram basic peculiarities but also the key experimental facts, related to the cuprate HTSC-materials

The medical use of radio frequency (RF) is based on an oscillating electrical current forcing collisions between charged molecules and ions, which are then transformed into heat. RF heating occurs irrespective of chromophore or skin type and is not dependent on selective photothermolysis. RF can be delivered using monopolar, bipolar, and unipolar devices, and each method has theoretical limits of depth penetration. A variant of bipolar delivery is fractional RF delivery. In monopolar configurations, RF will penetrate deeply and return via a grounding electrode. Multiple devices are available and are detailed later in the text. RF thermal stimulation is believed to result in a microinflammatory process that promotes new collagen. By manipulating skin cooling, RF can also be used for heating and reduction of fat. Currently, the most common uses of RF-based devices are to noninvasively manage and treat skin tightening of lax skin (including sagging jowls, abdomen, thighs, and arms), as well as wrinkle reduction, cellulite improvement, and body contouring.

Peer review of contour volume is a priority in the radiotherapy treatment quality assurance process for head and neck cancer. It is essential that incorporation of peer review activity does not introduce additional delays. An on-demand peer review process was piloted to assess the feasibility and efficiency of this approach, as compared with a historic scheduled weekly approach. Between November 2016 and April 2017 four head and neck clinicians in one centre took part in an on-demand peer review process. Cases were of radical or adjuvant intent of any histology and submitted on a voluntary basis. The outcome of contour peer review would be one of unchanged (UC), unchanged with variation or discretion noted (UV), minor change (M) or significant change (S). The time difference between the completion of the on-demand peer review was compared with the time difference to a hypothetical next Monday or Tuesday weekly peer review meeting. The time taken to review each case was also documented in the latter period of the pilot project. In total, 62 cases underwent peer review. Peer review on-demand provided dosimetrists with an average of an extra two working days available per case to meet treatment start dates. The proportion of cases with outcomes UC, UV, M and S were 45%, 16%, 26% and 13%, respectively. The mean peer review time spent per case was 17 min (12 cases). The main reason for S was discrepancy in imaging interpretation (4/8 cases). A lower proportion of oropharyngeal cases were submitted and had S outcomes. A higher proportion of complex cases, e.g. sinonasal/nasopharynx location or previous downstaging chemotherapy had S outcomes. The distribution of S outcomes appears to be similar regardless of clinician experience. The level of peer review activity among individuals differed by workload and job timetable. On-demand peer review of the head and neck contour volume is feasible, reduces delay to the start of dosimetry planning and bypasses the logistical

Objectives 1. To test whether alteration of the vocal fold medial surface contour can improve phonation. 2. To demonstrate that implant material properties affect vibration even when implant is deep to the vocal fold lamina propria. Study Design Induced phonation of excised human larynges. Methods Thirteen larynges were harvested within 24 hours post-mortem. Phonation threshold pressure (PTP) and flow (PTF) were measured before and after vocal fold injections using either calcium hydroxylapatite (CaHA) or hyaluronic acid (HA). Small-volume injections (median 0.0625 mL) were targeted to the infero-medial aspect of the thyroarytenoid (TA) muscle. Implant locations were assessed histologically. Results The effect of implantation on PTP was material-dependent. CaHA tended to increase PTP, whereas HA tended to decrease PTP (Wilcoxon test P = 0.00013 for onset). In contrast, the effect of implantation on PTF was similar, with both materials tending to decrease PTF (P = 0.16 for onset). Histology confirmed implant presence in the inferior half of the vocal fold vertical thickness. Conclusions Taken together, these data suggested the implants may have altered the vocal fold medial surface contour, potentially resulting in a less convergent or more rectangular glottal geometry as a means to improve phonation. An implant with a closer viscoelastic match to vocal fold cover is desirable for this purpose, as material properties can affect vibration even when the implant is not placed within the lamina propria. This result is consistent with theoretical predictions and implies greater need for surgical precision in implant placement and care in material selection. PMID:22865592

The purpose of this study was to determine the perceived and actual chin position(s) used for radiotherapy of head-and-neck cancers in a variety of clinical settings. Dosimetrists were asked to describe the external landmarks used to set the chin position. The lateral treatment planning radiographic figures in Ang's textbook, Radiotherapy for Head and Neck Cancers: Indications and Techniques, were analyzed for chin position by drawing a horizontal line from the tip of the chin to the cervical spine. The physicians at 7 departments were asked to rate the chin positions used in their departments for head-and-neck simulations. Choices included: (1) mildly flexed, (2) neutral, (3) mildly extended, and (4) hyperextended. In addition, each center was asked to select 2 representative cases to show routine chin position. The dosimetrists fixed the chin in neutral position by placing a virtual plane defined by 3 points (the base of the nasal septum [acanthus] and the external auditory canals) perpendicular to the table top. The type of head holder was irrelevant. Eighty-two percent (31/38) of the figures in Ang's text showed positioning in the neutral position (tip of the chin intersected the cervical spine between C2-3/C3-4). Most (71.4%) of the radiotherapists thought their patients were treated in the hyperextended neck position but, in fact, 85.7% (12/14) of the simulations showed a neural neck position. Reproducible chin positioning can be obtained by using the acanthiomeatal line. Consistent use of this technique will create a uniformly positioned set of axial co-images that have consistent appearance of avoidance and lymphatic areas. This will simplify contouring on axial computed tomography (CT) images of the neck. Standardizing the chin position is an important step to developing a standardized atlas and developing an information tool for automated contouring.

We have developed a new method of accurately profiling and measuring of a mask shape by utilizing a Mask CD-SEM. The method is intended to realize high accuracy, stability and reproducibility of the Mask CD-SEM adopting an edge detection algorithm as the key technology used in CD-SEM for high accuracy CD measurement. In comparison with a conventional image processing method for contour profiling, this edge detection method is possible to create the profiles with much higher accuracy which is comparable with CD-SEM for semiconductor device CD measurement. This method realizes two-dimensional metrology for refined pattern that had been difficult to measure conventionally by utilizing high precision contour profile. In this report, we will introduce the algorithm in general, the experimental results and the application in practice. As shrinkage of design rule for semiconductor device has further advanced, an aggressive OPC (Optical Proximity Correction) is indispensable in RET (Resolution Enhancement Technology). From the view point of DFM (Design for Manufacturability), a dramatic increase of data processing cost for advanced MDP (Mask Data Preparation) for instance and surge of mask making cost have become a big concern to the device manufacturers. This is to say, demands for quality is becoming strenuous because of enormous quantity of data growth with increasing of refined pattern on photo mask manufacture. In the result, massive amount of simulated error occurs on mask inspection that causes lengthening of mask production and inspection period, cost increasing, and long delivery time. In a sense, it is a trade-off between the high accuracy RET and the mask production cost, while it gives a significant impact on the semiconductor market centered around the mask business. To cope with the problem, we propose the best method of a DFM solution using two-dimensional metrology for refined pattern.

The main purpose of this thesis has been to investigate and develop methods suitable for study of resonance phenomena in nuclear and subatomic physics. Emphasis has been on the momentum space formulation of the Schrodinger equation. It has been shown; starting from the integral formulation of the Schrodinger equation, that an efficient way of obtaining a complete set of states including bound- antibound and resonant states is through the Contour Deformation Method. The strength of the Contour Deformation Method has been illustrated by studying a wide range of different cases in subatomic physics where resonance phenomena appear. These applications ranges from the case of a single-particle moving in a spherically symmetric field to the case of strong deformations of the field. Further, it has been studied how resonances may be solved for in complex potentials which models absorptive and emittive processes, using the Contour Deformation Method. The results obtained in these specific applications, strongly favour the Contour Deformation Method in comparison with other methods such as complex coordinate scaling and analytic continuation in the coupling strength. The most appealing feature of CD-NI is that not only does it give accurate results for resonances and anti-bound states, but in addition it provides us with a complete set of states which may be used in many different eigenfunction expansions. The only limitation of CDM is that the analytic structure of the potential has to be known, since the choice of contour is dictated by the singularity structure of the potential. The revival and study of CDM applied to nuclear physics, may be considered the main issue of the first part of this thesis, and is also the topic of Paper 1. In the second part of this thesis, the focus was directed towards the issue of how resonance phenomena may be understood in nuclei, when several valence particles are present. The newly developed Gamow Shell Model is a promising approach in

A prospecting system is described for hydrocarbons using emanoradiation measurements of the neutron, beta, gamma rays, and radon gas emitted at the earth surface and atmosphere from the earth basement complex and, the overlying sedimentary deposits of carbonaceous rocks, shales and sandstone that are impregnated with uranium, thorium and potassium derived from the eroded earth basement complex materials. A number of check points are measured and the radiation levels are plotted to form a georadiograph. A comparison between the background level and the check point levels is used in determining the contour data basically of the earth's stratosphere, altered in its variation by hydrocarbons, radiation active substances, and/or mineral deposits. 2 claims, 10 figures

We present Active Orientation Models (AOMs), generative models of facial shape and appearance, which extend the well-known paradigm of Active Appearance Models (AAMs) for the case of generic face alignment under unconstrained conditions. Robustness stems from the fact that the proposed AOMs employ a

Purpose: The purpose of this study was to evaluate the variability in target volume and organ at risk (OAR) contour delineation for retroperitoneal sarcoma (RPS) among 12 sarcoma radiation oncologists. Methods and Materials: Radiation planning computed tomography (CT) scans for 2 cases of RPS were distributed among 12 sarcoma radiation oncologists with instructions for contouring gross tumor volume (GTV), clinical target volume (CTV), high-risk CTV (HR CTV: area judged to be at high risk of resulting in positive margins after resection), and OARs: bowel bag, small bowel, colon, stomach, and duodenum. Analysis of contour agreement was performed using the simultaneous truth and performance level estimation (STAPLE) algorithm and kappa statistics. Results: Ten radiation oncologists contoured both RPS cases, 1 contoured only RPS1, and 1 contoured only RPS2 such that each case was contoured by 11 radiation oncologists. The first case (RPS 1) was a patient with a de-differentiated (DD) liposarcoma (LPS) with a predominant well-differentiated (WD) component, and the second case (RPS 2) was a patient with DD LPS made up almost entirely of a DD component. Contouring agreement for GTV and CTV contours was high. However, the agreement for HR CTVs was only moderate. For OARs, agreement for stomach, bowel bag, small bowel, and colon was high, but agreement for duodenum (distorted by tumor in one of these cases) was fair to moderate. Conclusions: For preoperative treatment of RPS, sarcoma radiation oncologists contoured GTV, CTV, and most OARs with a high level of agreement. HR CTV contours were more variable. Further clarification of this volume with the help of sarcoma surgical oncologists is necessary to reach consensus. More attention to delineation of the duodenum is also needed.

Purpose: The objective of this study is to determine whether there is less contouring variability of the prostate using higher-strength magnetic resonance images (MRI) compared with standard MRI and computed tomography (CT). Methods and Materials: Forty patients treated with prostate brachytherapy were accrued to a prospective study that included the acquisition of 1.5-T MR and CT images at specified time points. A subset of 10 patients had additional 3.0-T MR images acquired at the same time as their 1.5-T MR scans. Images from each of these patients were contoured by 5 radiation oncologists, with a random subset of patients repeated to quantify intraobserver contouring variability. To minimize bias in contouring the prostate, the image sets were placed in folders in a random order with all identifiers removed from the images. Results: Although there was less interobserver contouring variability in the overall prostate volumes in 1.5-T MRI compared with 3.0-T MRI (p < 0.01), there was no significant differences in contouring variability in the different regions of the prostate between 1.5-T MRI and 3.0-T MRI. MRI demonstrated significantly less interobserver contouring variability in both 1.5-T and 3.0-T compared with CT in overall prostate volumes (p < 0.01, p = 0.01), with the greatest benefits being appreciated in the base of the prostate. Overall, there was less intraobserver contouring variability than interobserver contouring variability for all of the measurements analyzed. Conclusions: Use of 3.0-T MRI does not demonstrate a significant improvement in contouring variability compared with 1.5-T MRI, although both magnetic strengths demonstrated less contouring variability compared with CT.

Purpose: The purpose of this study was to evaluate the variability in target volume and organ at risk (OAR) contour delineation for retroperitoneal sarcoma (RPS) among 12 sarcoma radiation oncologists. Methods and Materials: Radiation planning computed tomography (CT) scans for 2 cases of RPS were distributed among 12 sarcoma radiation oncologists with instructions for contouring gross tumor volume (GTV), clinical target volume (CTV), high-risk CTV (HR CTV: area judged to be at high risk of resulting in positive margins after resection), and OARs: bowel bag, small bowel, colon, stomach, and duodenum. Analysis of contour agreement was performed using the simultaneous truth and performance level estimation (STAPLE) algorithm and kappa statistics. Results: Ten radiation oncologists contoured both RPS cases, 1 contoured only RPS1, and 1 contoured only RPS2 such that each case was contoured by 11 radiation oncologists. The first case (RPS 1) was a patient with a de-differentiated (DD) liposarcoma (LPS) with a predominant well-differentiated (WD) component, and the second case (RPS 2) was a patient with DD LPS made up almost entirely of a DD component. Contouring agreement for GTV and CTV contours was high. However, the agreement for HR CTVs was only moderate. For OARs, agreement for stomach, bowel bag, small bowel, and colon was high, but agreement for duodenum (distorted by tumor in one of these cases) was fair to moderate. Conclusions: For preoperative treatment of RPS, sarcoma radiation oncologists contoured GTV, CTV, and most OARs with a high level of agreement. HR CTV contours were more variable. Further clarification of this volume with the help of sarcoma surgical oncologists is necessary to reach consensus. More attention to delineation of the duodenum is also needed

Inhomogeneous quantum critical systems in one spatial dimension have been studied by using conformal field theory in static curved backgrounds. Two interesting examples are the free fermion gas in the harmonic trap and the inhomogeneous XX spin chain called rainbow chain. For conformal field theories defined on static curved spacetimes characterised by a metric which is Weyl equivalent to the flat metric, with the Weyl factor depending only on the spatial coordinate, we study the entanglement hamiltonian and the entanglement spectrum of an interval adjacent to the boundary of a segment where the same boundary condition is imposed at the endpoints. A contour function for the entanglement entropies corresponding to this configuration is also considered, being closely related to the entanglement hamiltonian. The analytic expressions obtained by considering the curved spacetime which characterises the rainbow model have been checked against numerical data for the rainbow chain, finding an excellent agreement.

Accurate cardiac deformation analysis for cardiac displacement and strain imaging over time requires Lagrangian description of deformation of myocardial tissue structures. Failure to couple the estimated displacement and strain information with the correct myocardial tissue structures will lead to erroneous result in the displacement and strain distribution over time. Lagrangian based tracking in this paper divides the tissue structure into a fixed number of pixels whose deformation is tracked over the cardiac cycle. An algorithm that utilizes a polar-grid generated between the estimated endocardial and epicardial contours for cardiac short axis images is proposed to ensure Lagrangian description of the pixels. Displacement estimates from consecutive radiofrequency frames were then mapped onto the polar grid to obtain a distribution of the actual displacement that is mapped to the polar grid over time. A finite element based canine heart model coupled with an ultrasound simulation program was used to verify this approach. Segmental analysis of the accumulated displacement and strain over a cardiac cycle demonstrate excellent agreement between the ideal result obtained directly from the finite element model and our Lagrangian approach to strain estimation. Traditional Eulerian based estimation results, on the other hand, show significant deviation from the ideal result. An in vivo comparison of the displacement and strain estimated using parasternal short axis views is also presented. Lagrangian displacement tracking using a polar grid provides accurate tracking of myocardial deformation demonstrated using both finite element and in vivo radiofrequency data acquired on a volunteer. In addition to the cardiac application, this approach can also be utilized for transverse scans of arteries, where a polar grid can be generated between the contours delineating the outer and inner wall of the vessels from the blood flowing though the vessel.

Full Text Available Proposed linear and nonlinear regression models, which take into account the equation of trend and seasonality indices for the analysis and restore the volume of passenger traffic over the past period of time and its prediction for future years, as well as the algorithm of formation of these models based on statistical analysis over the years. The desired model is the first step for the synthesis of more complex models, which will enable forecasting of passenger (income level airline with the highest accuracy and time urgency.

The Activated Sludge Model No. 2d (ASM2d) presents a model for biological phosphorus removal with simultaneous nitrification-denitrification in activated sludge systems. ASM2d is based on ASM2 and is expanded to include the denitrifying activity of the phosphorus accumulating organisms (PAOs......). This extension of ASM2 allows for improved modeling of the processes, especially with respect to the dynamics of nitrate and phosphate. (C) 1999 IAWQ Published by Elsevier Science Ltd. All rights reserved....

Creation of DEVS models has been advanced through Model Driven Architecture and its frameworks. The overarching role of the frameworks has been to help develop model specifications in a disciplined fashion. Frameworks can provide intermediary layers between the higher level mathematical models...... and their corresponding software specifications from both structural and behavioral aspects. Unlike structural modeling, developing models to specify behavior of systems is known to be harder and more complex, particularly when operations with non-trivial control schemes are required. In this paper, we propose specifying...... activity-based behavior modeling of parallel DEVS atomic models. We consider UML activities and actions as fundamental units of behavior modeling, especially in the presence of recent advances in the UML 2.5 specifications. We describe in detail how to approach activitymodeling with a set of elemental...

... 47 Telecommunication 4 2010-10-01 2010-10-01 false Class A TV station protected contour. 73.6010... RADIO BROADCAST SERVICES Class A Television Broadcast Stations § 73.6010 Class A TV station protected contour. (a) A Class A TV station will be protected from interference within the following predicted...

A terrain M is the graph of a bivariate function. We assume that M is represented as a triangulated surface with N vertices. A contour (or isoline) of M is a connected component of a level set of M. Generically, each contour is a closed polygonal curve; at "critical" levels these curves may touch...

The problem of free convection in a thin porous contour, placed in uniform impermeable massif is considered. The approximate analitical solution of conjugate problem is obtained. The critical Rayleigh number is determined, by exceeding of which the steady fluid circulation in an annulus is established. The computations of abnormal heat flow near surface are carried out, stipulated by thermoconvection in a contour.

An experiment investigated the effect of tonal language background on discrimination of pitch contour in short spoken and musical items. It was hypothesized that extensive exposure to a tonal language attunes perception of pitch contour. Accuracy and reaction times of adult participants from tonal (Thai) and non-tonal (Australian English) language…

This paper proposes a novel iterative method of regularization with application of an advanced technique for detection of contours. To eliminate noises, the properties of convolution of functions are utilized. The method can be accomplished in a simple neural cellular network, which creates the possibility of extraction of contours by automatic image recognition equipment. (author)

Full Text Available Human observers can perceive the existence of a transparent surface from dynamic image deformation. They can also easily discriminate a transparent solid material such as plastic and glass from a transparent fluid one such as water and shampoo just by viewing them. However, the image information required for material discrimination of this sort is still unclear. A liquid changes its contour shape non-rigidly. We therefore examined whether additional properties of the contour of a deformation-defined region, which indicated contour non-rigidity, biased percepts of the region toward liquid materials. Our stimuli had a translating circular region wherein a natural texture image was deformed at the spatiotemporal deformation frequency that was optimal for the perception of a transparent layer. In Experiment 1, we dynamically deformed the contour of the circular region and found that large deformation of the contour biased the percept toward liquid. In Experiment 2, we manipulated the blurriness of the contour and observed that a strongly blurred contour biased percepts toward liquid. Taken together, the results suggest that a deforming region lacking a discrete contour biases percepts toward liquid.

A previous study found a visual deficit in contour integration in English readers with dyslexia (Simmers & Bex, 2001). Visual contour integration may play an even more significant role in Chinese handwriting particularly due to its logographic presentation (Lam, Au, Leung, & Li-Tsang, 2011). The current study examined the relationship…

Full Text Available The article considers the non­terminal problem for neutral contour of a telecontrolled pilotless aircraft. Optimal control synthesis is provided on the basis of minimization of generalized work functional. The analysis of optimal telecontrolled pilotless aircraft contour is carried out.

Problem Statement: The activated sludge system needs to improve the operational performance and to achieve more effective control. To realize this, a better quantitative understanding of the biofloc characteristics is required. The objectives of this study were to: (i) Study the biofloc characteristics from kinetics-mass transfer interaction point of view by quantification of the weight of the aerobic portion of the activated sludge floc to the total floc weight. (ii) Study the effect of bulk...

Pulse contour analysis of the noninvasive finger arterial pressure waveform provides a convenient means to estimate cardiac output (Q̇). The method has been compared with standard methods under a range of conditions but never before during spaceflight. We compared pulse contour analysis with the Modelflow algorithm to estimates of Q̇ obtained by rebreathing during preflight baseline testing and during the final month of long-duration spaceflight in nine healthy male astronauts. By Modelflow analysis, stroke volume was greater in supine baseline than seated baseline or inflight. Heart rate was reduced in supine baseline so that there were no differences in Q̇ by Modelflow estimate between the supine (7.02 ± 1.31 l/min, means ± SD), seated (6.60 ± 1.95 l/min), or inflight (5.91 ± 1.15 l/min) conditions. In contrast, rebreathing estimates of Q̇ increased from seated baseline (4.76 ± 0.67 l/min) to inflight (7.00 ± 1.39 l/min, significant interaction effect of method and spaceflight, P < 0.001). Pulse contour analysis utilizes a three-element Windkessel model that incorporates parameters dependent on aortic pressure-area relationships that are assumed to represent the entire circulation. We propose that a large increase in vascular compliance in the splanchnic circulation invalidates the model under conditions of spaceflight. Future spaceflight research measuring cardiac function needs to consider this important limitation for assessing absolute values of Q̇ and stroke volume. NEW & NOTEWORTHY Noninvasive assessment of cardiac function during human spaceflight is an important tool to monitor astronaut health. This study demonstrated that pulse contour analysis of finger arterial blood pressure to estimate cardiac output failed to track the 46% increase measured by a rebreathing method. These results strongly suggest that alternative methods not dependent on pulse contour analysis are required to track cardiac function in spaceflight

A new algorithm of segmenting contour series of images is presented, which can achieve three dimension reconstruction with parametric recognition in Reverse Engineering based on X-ray CT. First, in order to get the nested relationship between contours, a method of a certain angle ray is used. Second, for realizing the contour location in one slice, another approach is presented to generate the contour tree by scanning the relevant vector only once. Last, a judge algorithm is put forward to accomplish the contour match between slices by adopting the qualitative and quantitative properties. The example shows that this algorithm can segment contour series of CT parts rapidly and precisely. (authors)

The authors have analyzed the role of the thin contour in radiodiagnisis of various diseases of the gastric mucosa. Altogether 140 patients with various gastric diseases were investigated. Using X-ray examination of the stomach based on the common 2-phase method, thin contour images were obtained in 80 % of the cases. The results of the investigation have revealed direct correlation between the type of the thin contour and a morphological picture of the gastric mucosa in chronic gastritis. Early stomach cancer was characterized by the local absence or rearrangement of a usual pattern of the thin contour on stomach radiograms. It was difficult to defect single erosions or polyps with a diameter under 5 mm against a background of the gastric mucosa thin contour. Good visualization of stomach areolae, particularly those of a rough nodular type in the proximal part of the stomach was suggestive of an ulcerative lesion

A parametric model of the atmospheric transmittance in the PAR band is presented. The model can be straightforwardly applied for calculating the beam, diffuse and global components of the PAR solar irradiance. The required inputs are: air pressure, ozone, water vapor and nitrogen dioxide column content, Ångström's turbidity coefficient and single scattering albedo. Comparison with other models and ground measured data shows a reasonable level of accuracy for this model, making it suitable for practical applications. From the computational point of view the calculus is condensed into simple algebra which is a noticeable advantage. For users interested in speed-intensive computation of the effective PAR solar irradiance, a PC program based on the parametric equations along with a user guide are available online at http://solar.physics.uvt.ro/srms

Purpose/Objective(s): Current guidelines for esophageal cancer contouring are derived from traditional 2-dimensional fields based on bony landmarks, and they do not provide sufficient anatomic detail to ensure consistent contouring for more conformal radiation therapy techniques such as intensity modulated radiation therapy (IMRT). Therefore, we convened an expert panel with the specific aim to derive contouring guidelines and generate an atlas for the clinical target volume (CTV) in esophageal or gastroesophageal junction (GEJ) cancer. Methods and Materials: Eight expert academically based gastrointestinal radiation oncologists participated. Three sample cases were chosen: a GEJ cancer, a distal esophageal cancer, and a mid-upper esophageal cancer. Uniform computed tomographic (CT) simulation datasets and accompanying diagnostic positron emission tomographic/CT images were distributed to each expert, and the expert was instructed to generate gross tumor volume (GTV) and CTV contours for each case. All contours were aggregated and subjected to quantitative analysis to assess the degree of concordance between experts and to generate draft consensus contours. The panel then refined these contours to generate the contouring atlas. Results: The κ statistics indicated substantial agreement between panelists for each of the 3 test cases. A consensus CTV atlas was generated for the 3 test cases, each representing common anatomic presentations of esophageal cancer. The panel agreed on guidelines and principles to facilitate the generalizability of the atlas to individual cases. Conclusions: This expert panel successfully reached agreement on contouring guidelines for esophageal and GEJ IMRT and generated a reference CTV atlas. This atlas will serve as a reference for IMRT contours for clinical practice and prospective trial design. Subsequent patterns of failure analyses of clinical datasets using these guidelines may require modification in the future

The objective of this study was to develop and assess the feasibility of utilizing consensus-based penalty metrics for the purpose of critical structure and organ at risk (OAR) contouring quality assurance and improvement. A Delphi study was conducted to obtain consensus on contouring penalty metrics to assess trainee-generated OAR contours. Voxel-based penalty metric equations were used to score regions of discordance between trainee and expert contour sets. The utility of these penalty metric scores for objective feedback on contouring quality was assessed by using cases prepared for weekly radiation oncology radiation oncology trainee treatment planning rounds. In two Delphi rounds, six radiation oncology specialists reached agreement on clinical importance/impact and organ radiosensitivity as the two primary criteria for the creation of the Critical Structure Inter-comparison of Segmentation (CriSIS) penalty functions. Linear/quadratic penalty scoring functions (for over- and under-contouring) with one of four levels of severity (none, low, moderate and high) were assigned for each of 20 OARs in order to generate a CriSIS score when new OAR contours are compared with reference/expert standards. Six cases (central nervous system, head and neck, gastrointestinal, genitourinary, gynaecological and thoracic) then were used to validate 18 OAR metrics through comparison of trainee and expert contour sets using the consensus derived CriSIS functions. For 14 OARs, there was an improvement in CriSIS score post-educational intervention. The use of consensus-based contouring penalty metrics to provide quantitative information for contouring improvement is feasible.

Analyses of chemical reactions have been widely carried out for soluble fission products encountered in nuclear fuel reprocessing. For detailed analyses of reactions, a prediction of the activity or activity coefficient for nitric acid, water, and several nitrates of fission products is needed. An idea for the predicted nitric acid activity was presented earlier. The model, designated the hydration model, does not predict the nitrate activity. It did, however, suggest that the activity of water would be a function of nitric acid activity but not the molar fraction of water. If the activities of nitric acid and water are accurately predicted, the activity of the last component, nitrate, can be calculated using the Gibbs-Duhem relation for chemical potentials. Therefore, in this study, the earlier hydration model was modified to evaluate the water activity more accurately. The modified model was experimentally examined in stimulated reprocessing solutions. It is concluded that the modified model was suitable for water activity, but further improvement was needed for the activity evaluation of nitric acid in order to calculate the nitrate activity

Prostate cancer is one of the most common diseases treated in a radiation oncology department. One of the major predictors of the treatment outcome and patient side effects is the accuracy of the anatomical contours for the treatment plan. Therefore, the purpose of this study was to determine which anatomical structures are most often contoured correctly and incorrectly by medical dosimetry students. The author also wanted to discover whether a review of the contouring rules would increase contouring accuracy. To achieve this, a male computed tomography dataset consisting of 72 transverse slices was sent to students for contouring. The students were instructed to import this dataset into their treatment planning system and contour the following structures: skin, bladder, rectum, prostate, penile bulb, seminal vesicles, left femoral head, and right femoral head. Upon completion of the contours, the contour file was evaluated against a “gold standard” contour set using StructSure software (Standard Imaging, Inc). A review of the initial contour results was conducted and then students were instructed to contour the dataset a second time. The results of this study showed significant differences between contouring sessions. These results and the standardization of contouring rules should benefit all individuals who participate in the treatment planning of cancer patients.

The development of novel form-active hybrid structures (FAHS) is impeded by a lack of modelling tools that allow for exploratory topology modelling of shaped assemblies. We present a flexible and real-time computational design modelling pipeline developed for the exploratory modelling of FAHS...... that enables designers and engineers to iteratively construct and manipulate form-active hybrid assembly topology on the fly. The pipeline implements Kangaroo2's projection-based methods for modelling hybrid structures consisting of slender beams and cable networks. A selection of design modelling sketches...

Over the past several decades, the technology of micro-electromechanical system (MEMS) has advanced. A clear need of miniaturization and integration of electronics components has had new solutions for the next generation of wireless communications. The aluminum nitride (AlN) MEMS contour-mode resonator (CMR) has emerged and become promising and competitive due to the advantages of the small size, high quality factor and frequency, low resistance, compatibility with integrated circuit (IC) technology, and the ability of integrating multi-frequency devices on a single chip. In this article, a comprehensive review of AlN MEMS CMR technology will be presented, including its basic working principle, main structures, fabrication processes, and methods of performance optimization. Among these, the deposition and etching process of the AlN film will be specially emphasized and recent advances in various performance optimization methods of the CMR will be given through specific examples which are mainly focused on temperature compensation and reducing anchor losses. This review will conclude with an assessment of the challenges and future trends of the CMR. Project supported by National Natural Science Foundation (Nos. 61274001, 61234007, 61504130), the Nurturing and Development Special Projects of Beijing Science and Technology Innovation Base's Financial Support (No. Z131103002813070), and the National Defense Science and Technology Innovation Fund of CAS (No. CXJJ-14-M32).

We propose a semi-Lagrangian method for multiphase interface tracking. In contrast to previous methods, our method maintains an explicit polygonal mesh, which is reconstructed from an unsigned distance function and an indicator function, to track the interface of arbitrary number of phases. The surface mesh is reconstructed at each step using an efficient multiphase polygonization procedure with precomputed stencils while the distance and indicator function are updated with an accurate semi-Lagrangian path tracing from the meshes of the last step. Furthermore, we provide an adaptive data structure, multiphase distance tree, to accelerate the updating of both the distance function and the indicator function. In addition, the adaptive structure also enables us to contour the distance tree accurately with simple bisection techniques. The major advantage of our method is that it can easily handle topological changes without ambiguities and preserve both the sharp features and the volume well. We will evaluate its efficiency, accuracy and robustness in the results part with several examples.

According to data from GLOBOCAN (IARC) at 2012, breast cancer was the highest rated of new cancer case by 43.3 % (after controlled by age), with mortality rated as high as 12.9 %. Oncology is a major field which focusing on improving the development of drug and therapeutics cancer in pharmaceutical and biotechnology companies. Nowadays, many researchers lead to computational chemistry and bioinformatic for pharmacophore generation. A pharmacophore describes as a group of atoms in the molecule which is considered to be responsible for a pharmacological action. Prediction of biological function from chemical structure in silico modeling reduces the use of chemical reagents so the risk of environmental pollution decreased. In this research, we proposed QSAR model to analyze the composition of cancer drugs which assumed to be homogenous in character and treatment. Atomic interactions which analyzed are learned through parameters such as log p as descriptors hydrophobic, n_poinas descriptor contour strength and molecular structure, and also various concentrations inhibitor (micromolar and nanomolar) from NCBI drugs bank. The differences inhibitor activity was observed by the presence of IC 50 residues value from inhibitor substances at various concentration. Then, we got a general overview of the state of safety for drug stability seen from its IC 50 value. In our study, we also compared between micromolar and nanomolar inhibitor effect from QSAR model results. The QSAR model analysis shows that the drug concentration with nanomolar is better than micromolar, related with the content of inhibitor substances concentration. This QSAR model got the equation: Log 1/IC50 = (0.284) (±0.195) logP + (0.02) (±0.012) n_poin + (-0.005) (±0.083) Inhibition10.2nanoM + (0.1) (±0.079) Inhibition30.5nanoM + (-0.016) (±0.045) Inhibition91.5nanoM + (-2.572) (±1.570) (n = 13; r = 0.813; r2 = 0.660; s = 0.764; F = 2.720; q2 = 0.660).

Existing activity-based models of travel demand consider a day as the time unit of observation and predict activity patterns of inhviduals for a typical or average day. In this study we argue that the use of a time span of one day severely limits the ability of the models to predict responsive

China-made 5-axis simultaneous contouring CNC machine tool and domestically developed industrial computer-aided manufacture (CAM) technology were used for full crown fabrication and measurement of crown accuracy, with an attempt to establish an open CAM system for dental processing and to promote the introduction of domestic dental computer-aided design (CAD)/CAM system. Commercially available scanning equipment was used to make a basic digital tooth model after preparation of crown, and CAD software that comes with the scanning device was employed to design the crown by using domestic industrial CAM software to process the crown data in order to generate a solid model for machining purpose, and then China-made 5-axis simultaneous contouring CNC machine tool was used to complete machining of the whole crown and the internal accuracy of the crown internal was measured by using 3D-MicroCT. The results showed that China-made 5-axis simultaneous contouring CNC machine tool in combination with domestic industrial CAM technology can be used for crown making and the crown was well positioned in die. The internal accuracy was successfully measured by using 3D-MicroCT. It is concluded that an open CAM system for dentistry on the basis of China-made 5-axis simultaneous contouring CNC machine tool and domestic industrial CAM software has been established, and development of the system will promote the introduction of domestically-produced dental CAD/CAM system.

Activity landscapes (ALs) are representations and models of compound data sets annotated with a target-specific activity. In contrast to quantitative structure-activity relationship (QSAR) models, ALs aim at characterizing structure-activity relationships (SARs) on a large-scale level encompassing all active compounds for specific targets. The popularity of AL modeling has grown substantially with the public availability of large activity-annotated compound data sets. AL modeling crucially depends on molecular representations and similarity metrics used to assess structural similarity. Areas covered: The concepts of AL modeling are introduced and its basis in quantitatively assessing molecular similarity is discussed. The different types of AL modeling approaches are introduced. AL designs can broadly be divided into three categories: compound-pair based, dimensionality reduction, and network approaches. Recent developments for each of these categories are discussed focusing on the application of mathematical, statistical, and machine learning tools for AL modeling. AL modeling using chemical space networks is covered in more detail. Expert opinion: AL modeling has remained a largely descriptive approach for the analysis of SARs. Beyond mere visualization, the application of analytical tools from statistics, machine learning and network theory has aided in the sophistication of AL designs and provides a step forward in transforming ALs from descriptive to predictive tools. To this end, optimizing representations that encode activity relevant features of molecules might prove to be a crucial step.

Because of the numerous entities interacting, the complexity of the networks that regulate cell fate makes it impossible to analyze and understand them using the human brain alone. Computational modeling is a powerful method to unravel complex systems. We recently described the development of a

A two-system no-overlap model for rotatory strength is developed for electric-dipole forbidden as well as allowed transitions. General equations which allow for full utilization of symmetry in the chromophore and in the environment are obtained. The electron correlation terms are developed in full...

Purpose: To develop a practical approach for accurate contour deformation when deformable image registration (DIR) is used for atlas-based segmentation or contour propagation in image-guided radiotherapy. Methods: A contour deformation approach was developed on the basis of 3D mesh operations. The 2D contours represented by a series of points in each slice were first converted to a 3D triangular mesh, which was deformed by the deformation vectors resulting from DIR. A set of parallel 2D planes then cut through the deformed 3D mesh, generating unordered points and line segments, which should be reorganized into a set of 2D contour points. It was realized that the reorganization problem was equivalent to solving the Chinese Postman Problem (CPP) by traversing a graph built from the unordered points with the least cost. Alternatively, deformation could be applied to a binary mask converted from the original contours. The deformed binary mask was then converted back into contours at the CT slice locations. We performed a qualitative comparison to validate the mesh-based approach against the image-based approach. Results: The DIR could considerably change the 3D mesh, making complicated 2D contour representations after deformation. CPP was able to effectively reorganize the points in 2D planes no matter how complicated the 2D contours were. The mesh-based approach did not require a post-processing of the contour, thus accurately showing the actual deformation in DIR. The mesh-based approach could keep some fine details and resulted in smoother contours than the image-based approach did, especially for the lung structure. Image-based approach appeared to over-process contours and suffered from image resolution limits. The mesh-based approach was integrated into in-house DIR software for use in routine clinic and research. Conclusion: We developed a practical approach for accurate contour deformation. The efficiency of this approach was demonstrated in both clinic and

Full Text Available This study aims at managing activity carried out in Computer-Supported Collaborative Learning (CSCL environments. We apply an approach that gathers and manages the knowledge underlying huge data structures, resulting from collaborative interaction among participants and stored as activity logs. Our method comprises a variety of important issues and aspects, such as: deep understanding of collaboration among participants in workgroups, definition of an ontology for providing meaning to isolated data manifestations, discovering of knowledge structures built in huge amounts of data stored in log files, and development of high-semantic indicators to describe diverse primitive collaborative acts, and binding these indicators to formal descriptions defined in the collaboration ontology; besides our method includes gathering collaboration indicators from web forums using natural language processing (NLP techniques.

The nature of human-human interaction, specifically, how people synchronize with each other in multiple-participant conversations, is described by a ferromagnetic interaction model of people’s activity levels. We found two microscopic human interaction characteristics from a real-environment face-to-face conversation. The first characteristic is that people quite regularly synchronize their activity level with that of the other participants in a conversation. The second characteristic is that the degree of synchronization increases as the number of participants increases. Based on these microscopic ferromagnetic characteristics, a “conversation activity level” was modeled according to the Ising model. The results of a simulation of activity level based on this model well reproduce macroscopic experimental measurements of activity level. This model will give a new insight into how people interact with each other in a conversation.

As a service composition language, BPEL imposes as constraint that a business process model should consist only of activities for interacting with other business processes. BPEL provides limited support for implementing internal activities, i.e. activities that are performed by a single business

Spontaneous rhythmic activity occurs in many developing neural networks. The activity in these hyperexcitable networks is comprised of recurring "episodes" consisting of "cycles" of high activity that alternate with "silent phases" with little or no activity. We introduce a new model of synaptic...... dynamics that takes into account that only a fraction of the vesicles stored in a synaptic terminal is readily available for release. We show that our model can reproduce spontaneous rhythmic activity with the same general features as observed in experiments, including a positive correlation between...

Basic notions making it possible to study and simulate the peculiarities of man-operator activity, in particular his way of thiking, are considered. Special attention is paid to cognitive models based on concept of decisive role of knowledge (its acquisition, storage and application) in the man mental processes and activity. The models are based on three basic notions, which are the professional world image, activity strategy and spontaneous decisions

Full Text Available (deliberative attitudes) (Pokahr, 2005). The BDI model does not cover emotional and other ‘higher’ human attitudes. KRONOS is a generic Computational Building Simulation (CBS) tool that was developed over the past three years to work on advanced... featured, stable, mature and platform independent with an easy to use C/C++ Application Program Interface (API). It has advanced joint types and integrated collision detection with friction. ODE is particularly useful for simulating vehicles, objects...

We propose a new active mask algorithm for the segmentation of fluorescence microscope images of punctate patterns. It combines the (a) flexibility offered by active-contour methods, (b) speed offered by multiresolution methods, (c) smoothing offered by multiscale methods, and (d) statistical modeling offered by region-growing methods into a fast and accurate segmentation tool. The framework moves from the idea of the "contour" to that of "inside and outside," or masks, allowing for easy multidimensional segmentation. It adapts to the topology of the image through the use of multiple masks. The algorithm is almost invariant under initialization, allowing for random initialization, and uses a few easily tunable parameters. Experiments show that the active mask algorithm matches the ground truth well and outperforms the algorithm widely used in fluorescence microscopy, seeded watershed, both qualitatively, as well as quantitatively.

After drawing and stacking contours of a structure, which is identified in the serially sectioned images, three-dimensional (3D) image can be made by surface reconstruction. Usually, software is composed for the surface reconstruction. In order to compose the software, medical doctors have to acquire the help of computer engineers. So in this research, surface reconstruction of stacked contours was tried by using commercial software. The purpose of this research is to enable medical doctors to perform surface reconstruction to make 3D images by themselves. The materials of this research were 996 anatomic images (1 mm intervals) of left lower limb, which were made by serial sectioning of a cadaver. On the Adobe Photoshop, contours of 114 anatomic structures were drawn, which were exported to Adobe Illustrator files. On the Maya, contours of each anatomic structure were stacked. On the Rhino, superoinferior lines were drawn along all stacked contours to fill quadrangular surfaces between contours. On the Maya, the contours were deleted. 3D images of 114 anatomic structures were assembled with their original locations preserved. With the surface reconstruction technique, developed in this research, medical doctors themselves could make 3D images of the serially sectioned images such as CTs and MRIs.

Although aesthetic procedures are known to have a higher impact on women, men are becoming more inclined toward such procedures since the last decade. To determine the reason behind the increase in demand for male aesthetic procedures and to learn about the expectations and inquietude related to body contouring surgery, a prospective questionnaire study was conducted on 200 Turkish males from January 1, 2011-May 31, 2012. Demographic information, previous aesthetic procedures and thoughts on body contouring procedures with given reasons were questioned. The results of the study showed that 53 % of all participants considered undergoing body contouring surgery with the given reason that they believed their current body structure required it. For those who did not consider contouring operations, 92.5 % said they felt that they did not need such a procedure. The results of the statistical analysis showed that BMI was a significant factor in the decision making process for wanting to undergo body contouring procedures. The results of the study showed that men's consideration for aesthetic operations depends mainly on necessity and that the most considered region was the abdominal zone in regard to contouring. We can conclude that men are becoming more interested in body contouring operations and therefore different surgical procedures should be refined and re-defined according to the expectations of this new patient group.

Full Text Available Background: Three-dimensional (3D images could provide more accurate evaluation for facial attractiveness than two-dimensional (2D images. The 3D facial image could be simplified into gray scale 3D contour lines. Whether female facial attractiveness could be perceived in these simplified 3D facial contour lines should be determined. Methods: A series of 100 2D photographs (one frontal and two lateral views and 3D contour lines extracted from 3D facial images of females were projected onto a screen. Each image presentation lasted 5 s, and the evaluators marked their impression of each image’s facial attractiveness on a five-point Likert scale within 3 s of its presentation. The evaluation of the 3D contour lines was performed twice, 2 weeks apart. The evaluators were university students. Results: High consistency (r = 0.92 was found for the first and second evaluation of 3D facial contour lines for female facial attractiveness. The judgments of unattractive face were more consistent than the judgments of attractive face. Male students tended to give lower scores than female students in the evaluation of female facial attractiveness. Conclusions: Female facial attractiveness could be evaluated by 3D facial contour lines. 3D facial contour lines should be one of the key factors of facial attractiveness.

The wormlike chain (WLC) model currently provides the best description of double-stranded DNA elasticity for micron-sized molecules. This theory requires two intrinsic material parameters-the contour length L and the persistence length p. We measured and then analyzed the elasticity of double-stranded DNA as a function of L (632 nm-7.03 microm) using the classic solution to the WLC model. When the elasticity data were analyzed using this solution, the resulting fitted value for the persistence length p(wlc) depended on L; even for moderately long DNA molecules (L = 1300 nm), this apparent persistence length was 10% smaller than its limiting value for long DNA. Because p is a material parameter, and cannot depend on length, we sought a new solution to the WLC model, which we call the "finite wormlike chain (FWLC)," to account for effects not considered in the classic solution. Specifically we accounted for the finite chain length, the chain-end boundary conditions, and the bead rotational fluctuations inherent in optical trapping assays where beads are used to apply the force. After incorporating these corrections, we used our FWLC solution to generate force-extension curves, and then fit those curves with the classic WLC solution, as done in the standard experimental analysis. These results qualitatively reproduced the apparent dependence of p(wlc) on L seen in experimental data when analyzed with the classic WLC solution. Directly fitting experimental data to the FWLC solution reduces the apparent dependence of p(fwlc) on L by a factor of 3. Thus, the FWLC solution provides a significantly improved theoretical framework in which to analyze single-molecule experiments over a broad range of experimentally accessible DNA lengths, including both short (a few hundred nanometers in contour length) and very long (microns in contour length) molecules.

Background. Fish species may be identified based on their unique otolith shape or contour. Several pattern recognition methods have been proposed to classify fish species through morphological features of the otolith contours. However, there has been no fully-automated species identification model with the accuracy higher than 80%. The purpose of the current study is to develop a fully-automated model, based on the otolith contours, to identify the fish species with the high classification accuracy. Methods. Images of the right sagittal otoliths of 14 fish species from three families namely Sciaenidae, Ariidae, and Engraulidae were used to develop the proposed identification model. Short-time Fourier transform (STFT) was used, for the first time in the area of otolith shape analysis, to extract important features of the otolith contours. Discriminant Analysis (DA), as a classification technique, was used to train and test the model based on the extracted features. Results. Performance of the model was demonstrated using species from three families separately, as well as all species combined. Overall classification accuracy of the model was greater than 90% for all cases. In addition, effects of STFT variables on the performance of the identification model were explored in this study. Conclusions. Short-time Fourier transform could determine important features of the otolith outlines. The fully-automated model proposed in this study (STFT-DA) could predict species of an unknown specimen with acceptable identification accuracy. The model codes can be accessed at http://mybiodiversityontologies.um.edu.my/Otolith/ and https://peerj.com/preprints/1517/. The current model has flexibility to be used for more species and families in future studies.

Purpose: Anatomy contouring is critical in radiation therapy. Inaccuracy and variation in defining critical volumes will affect everything downstream: treatment planning, dose-volume histogram analysis, and contour-based visual guidance used in image-guided radiation therapy. This study quantified: (1) variation in the contouring of organs at risk (OAR) in a clinical test case and (2) corresponding effects on dosimetric metrics of highly conformal plans. Methods and Materials: A common CT data set with predefined targets from a patient with oropharyngeal cancer was provided to a population of clinics, which were asked to (1) contour OARs and (2) design an intensity-modulated radiation therapy plan. Thirty-two acceptable plans were submitted as DICOM RT data sets, each generated by a different clinical team. Using those data sets, we quantified: (1) the OAR contouring variation and (2) the impact this variation has on dosimetric metrics. New technologies were employed, including a software tool to quantify three-dimensional structure comparisons. Results: There was significant interclinician variation in OAR contouring. The degree of variation is organ-dependent. We found substantial dose differences resulting strictly from contouring variation (differences ranging from -289% to 56% for mean OAR dose; -22% to 35% for maximum dose). However, there appears to be a threshold in the OAR comparison metric beyond which the dose differences stabilize. Conclusions: The effects of interclinician variation in contouring organs-at-risk in the head and neck can be large and are organ-specific. Physicians need to be aware of the effect that variation in OAR contouring can play on the final treatment plan and not restrict their focus only to the target volumes.

Purpose: To define a male and female pelvic normal tissue contouring atlas for Radiation Therapy Oncology Group (RTOG) trials. Methods and Materials: One male pelvis computed tomography (CT) data set and one female pelvis CT data set were shared via the Image-Guided Therapy QA Center. A total of 16 radiation oncologists participated. The following organs at risk were contoured in both CT sets: anus, anorectum, rectum (gastrointestinal and genitourinary definitions), bowel NOS (not otherwise specified), small bowel, large bowel, and proximal femurs. The following were contoured in the male set only: bladder, prostate, seminal vesicles, and penile bulb. The following were contoured in the female set only: uterus, cervix, and ovaries. A computer program used the binomial distribution to generate 95% group consensus contours. These contours and definitions were then reviewed by the group and modified. Results: The panel achieved consensus definitions for pelvic normal tissue contouring in RTOG trials with these standardized names: Rectum, AnoRectum, SmallBowel, Colon, BowelBag, Bladder, UteroCervix, Adnexa{sub R}, Adnexa{sub L}, Prostate, SeminalVesc, PenileBulb, Femur{sub R}, and Femur{sub L}. Two additional normal structures whose purpose is to serve as targets in anal and rectal cancer were defined: AnoRectumSig and Mesorectum. Detailed target volume contouring guidelines and images are discussed. Conclusions: Consensus guidelines for pelvic normal tissue contouring were reached and are available as a CT image atlas on the RTOG Web site. This will allow uniformity in defining normal tissues for clinical trials delivering pelvic radiation and will facilitate future normal tissue complication research.

in a dynamic model of an active gas bearing and subsequent control loop design. A grey box model is determined based on experiments where piezo actuated valves are used to perturb the journal and hence excite the rotor-bearing system. Such modelling from actuator to output is shown to effciently support...

Various aspects of numerical modeling of Active Magnetic Regeneration (AMR) are presented. Using a 2-dimensional numerical model for solving the unsteady heat transfer equations for the AMR system, a range of physical effects on both idealized and non-idealized AMR are investigated. The modeled...

Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type.

Mathematical process modeling and biokinetics of activated sludge process were reviewed considering different types of models. It has been evaluated the task group models of ASMI. and 2, and 3 versioned by Henze et al considering the conditions of each model and the different processes of which every model consists. It is revealed that ASMI contains some defects avoided in ASM3. Relied on homogeneity, Models can be classified into homogenous models characterized by taking the activated sludge process as one phase. In this type of models, the internal mass transfer inside the floes was neglected.. Hence, the kinetic parameter produces can be considered inaccurate. The other type of models is the heterogeneous model This type considers the mass transfer operations in addition to the biochemical reaction processes; hence, the resulted kinetic parameters can be considered more accurate than that of homogenous type

Full Text Available The arterial pulse wave (APW has a distinct morphology whose contours reflect dynamics in cardiac function and peripheral vascular tone as a result of sympathetic nervous system (SNS control. With a transition from rest to increased metabolic demand, the expected augmentation of SNS outflow will not only affect arterial blood pressure and heart rate, it will also induce changes to the contours of the APW. Following a sports concussion, a transient state cardiovascular autonomic dysfunction is present. How this state affects the APW, has yet to be described. A prospective, parallel-group study on cardiovascular autonomic control (i.e., digital electrocardiogram and continuous beat-to-beat blood pressure was performed in the seated upright position in ten athletes with concussion and 7 non-injured control athletes. Changes in APW were compared at rest and during the first 60 seconds (F60 of an isometric handgrip test (IHGT in concussed athletes and non-injured controls within 48 hours (48hr and 1 week (1wk of injury. The concussion group was further separated by the length of time until they were permitted to return to play (RTP>1wk; RTP≤1wk. SysSlope, an indirect measurement of stroke volume, was significantly lower in the concussion group at rest and during F60 at 48hr and 1wk; a paradoxical decline in SysSlope occurred at each visit during the transition from rest to IHGT F60. The RTP>1wk group had lower SysSlope (405±200; 420±88; 454±236 mmHg/s, respectively at rest 48hr compared to the RTP≤1wk and controls. Similarly at 48hr rest, several measurements of arterial stiffness were abnormal in RTP>1wk compared to RTP≤1wk and controls: Peak-to-Notch Latency (0.12±0.04; 0.16±0.02; 0.17±0.05, respectively, Notch Relative Amplitude (0.70±0.03; 0.71±0.04; 0.66±0.14, respectively and Stiffness Index (6.4±0.2; 5.7±0.4; 5.8±0.5, respectively. Use of APW revealed that concussed athletes have a transient increase in peripheral artery

The procedure of recognition can be described as follows: There is a set of complex signals stored in the memory. Choosing one of these signals may be interpreted as generating a hypothesis concerning an 'expexted view of the world'. Then the brain compares a signal arising from our senses with the signal chosen from the memory leading to a change of the state of both signals. Furthermore, measurements of that procedure like EEG or MEG are based on the fact that recognition of signals causes a certain loss of excited neurons, i.e. the neurons change their state from 'excited' to 'nonexcited'. For that reason a statistical model of the recognition process should reflect both--the change of the signals and the loss of excited neurons. A first attempt to explain the process of recognition in terms of quantum statistics was given. In the present note it is not possible to present this approach in detail. In lieu we will sketch roughly a few of the basic ideas and structures of the proposed model of the recognition process (Section). Further, we introduce the basic spaces and justify the choice of spaces used in this approach. A more elaborate presentation including all proofs will be given in a series of some forthcoming papers. In this series also the procedures of creation of signals from the memory, amplification, accumulation and transformation of input signals, and measurements like EEG and MEG will be treated in detail

Human activity plays a central role in understanding large-scale social dynamics. It is well documented that individual activity pattern follows bursty dynamics characterized by heavy-tailed interevent time distributions. Here we study a large-scale online chatting dataset consisting of 5,549,570 users, finding that individual activity pattern varies with timescales whereas existing models only approximate empirical observations within a limited timescale. We propose a novel approach that models the intensity rate of an individual triggering an activity. We demonstrate that the model precisely captures corresponding human dynamics across multiple timescales over five orders of magnitudes. Our model also allows extracting the population heterogeneity of activity patterns, characterized by a set of individual-specific ingredients. Integrating our approach with social interactions leads to a wide range of implications.

The subject of axial contour of artificial crowns has and continues to be highly controversial. Much of the controversy centers arounrj whether the gingival sulcus is really in need of protection from buccal and/or lingual convexities, or whether a flatter emergence profile affords self cleansing muscle action. Evidence is reviewed in this part which suggests that overcontouring is probably more detrimental to gingival health than undercontouring. The critical role played by proper tooth reduction in attaining correct axial contour is shown and a rationale presented for the important interplay between preparation design, properties of the restorative materials to be employed and physiologic contour. (author)

This unique book is the key to computer contouring, exploring in detail the practice and principles using a personal computer. Contouring allows a three dimensional view in two dimensions and is a fundamental technique to represent spatial data. All aspects of this type of representation are covered including data preparation, selecting contour intervals, interpolation and griding, computing volumes and output and display. Formulated for both the novice and the experienced user, this book initially conducts the reader through a step by step explanation of PC software and its application to per

Multiple studies suggest that radiation dose to the area of the brainstem called the “dorsal vagal complex (DVC)” influences the frequency of nausea and vomiting during radiotherapy. The purpose of this didactic article is to describe the step-by-step process that we use to contour the general area of the DVC on axial computed tomography (CT) images as would be done for radiotherapy planning. The contouring procedure that we describe for contouring the area of the DVC is useful to medical dosimetrists and radiation oncologists.

Yucca Mountain, Nevada is underlain by 14.0 to 11.6 Ma volcanic rocks tilted eastward 3 degree to 20 degree and cut by faults that were primarily active between 12.7 and 11.6 Ma. A three-dimensional computer-based model of the central block of the mountain consists of seven structural subblocks composed of six formations and the interstratified-bedded tuffaceous deposits. Rocks from the 12.7 Ma Tiva Canyon Tuff, which forms most of the exposed rocks on the mountain, to the 13.1 Ma Prow Pass Tuff are modeled with 13 surfaces. Modeled units represent single formations such as the Pah Canyon Tuff, grouped units such as the combination of the Yucca Mountain Tuff with the superjacent bedded tuff, and divisions of the Topopah Spring Tuff such as the crystal-poor vitrophyre interval. The model is based on data from 75 boreholes from which a structure contour map at the base of the Tiva Canyon Tuff and isochore maps for each unit are constructed to serve as primary input. Modeling consists of an iterative cycle that begins with the primary structure-contour map from which isochore values of the subjacent model unit are subtracted to produce the structure contour map on the base of the unit. This new structure contour map forms the input for another cycle of isochore subtraction to produce the next structure contour map. In this method of solids modeling, the model units are presented by surfaces (structure contour maps), and all surfaces are stored in the model. Surfaces can be converted to form volumes of model units with additional effort. This lithostratigraphic and structural model can be used for (1) storing data from, and planning future, site characterization activities, (2) preliminary geometry of units for design of Exploratory Studies Facility and potential repository, and (3) performance assessment evaluations